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Transaction

3/7/2022 05:06:33 AM
ID: 80fb55586d...395d
Inputs (29)
#0
0d6b8a7bbacc...a145
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
2.97 ERG
#1
bbab92220c0f...4375
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
1.17 ERG
#2
bd48e75e3ad3...c857
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
5.9 ERG
#3
eb68c16c30db...65bd
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.219 ERG
#4
c2955bad85c3...f281
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
2.09 ERG
#5
cb7f156131dd...8690
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.908 ERG
#6
bebb5101ca38...3cfd
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.078 ERG
#7
7a3e87c1c27c...928e
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.761 ERG
#8
c811c475be6d...2c58
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
2.51 ERG
#9
0067bd8f8602...a1c5
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
1.46 ERG
#10
9e5b27ae078b...9461
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
2.52 ERG
#11
39796a66a25a...fb2a
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
6.39 ERG
#12
9439baea8b3a...3cf0
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.719 ERG
#13
34030aab3754...cf89
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
2.62 ERG
#14
e239119fd28f...d0fc
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.757 ERG
#15
7398f3daf0e9...2aae
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.956 ERG
#16
f19174610a12...af1f
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
1.25 ERG
#17
2d6189cb18a7...776b
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
1.1 ERG
#18
5c333cb9c636...e7ad
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
3.49 ERG
#19
ca2332579d8a...0cd2
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.294 ERG
#20
80ef645c28a0...4076
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
4.09 ERG
#21
55e99a0aab95...0a1d
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
1.51 ERG
#22
d6d15ef573ad...87fa
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
5.71 ERG
#23
5455a6ae608a...a896
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
1.39 ERG
#24
df3374f757cf...ffd4
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
0.966 ERG
#25
8fbc8b262354...c267
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
8.31 ERG
#26
b682277295cc...adb3
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
1.74 ERG
#27
20de342cb855...03c5
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
2.55 ERG
#28
45c86c452f0e...5175
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
c288d6a65a59...389a
Settlement height:
700,686
Value:
2.05 ERG
Outputs (30)
#0
9a986d6c5e34...2c11
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
11ffc4f81f55...52da
Settlement height:
700,686
Value:
2.97 ERG
#1
b58120684fd4...1e02
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
e0876dff0379...cfa4
Settlement height:
700,686
Value:
1.17 ERG
#2
ac04eea316fb...02ba
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
975756a308e8...866f
Settlement height:
700,686
Value:
5.89 ERG
#3
1af7421de9c7...e89c
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
078d851d8000...4250
Settlement height:
700,686
Value:
0.214 ERG
#4
641653c93f96...7055
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
105aa81854f1...0163
Settlement height:
700,686
Value:
2.09 ERG
#5
6759b29577f3...0e45
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
f3a5f5c9163c...758f
Settlement height:
700,686
Value:
0.903 ERG
#6
f18869b34865...9436
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
3b1813282745...8057
Settlement height:
700,686
Value:
0.073 ERG
#7
cf246a1084c5...1a86
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
5c7ee8f2ac49...b0a7
Settlement height:
700,686
Value:
0.756 ERG
#8
fea1b6b69bda...9cbb
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
7aee841b14fe...ac90
Settlement height:
700,686
Value:
2.51 ERG
#9
03ad7748035d...b371
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
5e508403e8d5...6aa6
Settlement height:
700,686
Value:
1.46 ERG
#10
4c521c4f9ece...40d2
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
a3a60c02aa72...664c
Settlement height:
700,686
Value:
2.52 ERG
#11
b8b518163675...fb44
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
b73cdc54de76...7902
Settlement height:
700,686
Value:
6.39 ERG
#12
71f7ad7efa43...6b2b
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
56d27ae170e5...9f6d
Settlement height:
700,686
Value:
0.714 ERG
#13
009b9a85cd41...5af7
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
45df7a86cbbd...a989
Settlement height:
700,686
Value:
2.61 ERG
#14
a2bf1b1a5371...794a
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
e8b941132b9e...f0c1
Settlement height:
700,686
Value:
0.752 ERG
#15
0e7e2862211f...be1d
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
44efaa38db87...1d26
Settlement height:
700,686
Value:
0.951 ERG
#16
20ce019d50e8...8d7d
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
02abc2cb1cb8...4166
Settlement height:
700,686
Value:
1.25 ERG
#17
2db93d8ea6d0...31e6
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
0e1296486455...58ec
Settlement height:
700,686
Value:
1.09 ERG
#18
9484dd06e7ef...97e2
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
47d1bf30da9a...b2a8
Settlement height:
700,686
Value:
3.48 ERG
#19
e9ba5da9b50d...1d90
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
0595e171b77d...2f6e
Settlement height:
700,686
Value:
0.289 ERG
#20
1b6e092b0ce2...c854
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
3d33c930bf40...16e5
Settlement height:
700,686
Value:
4.08 ERG
#21
a9a4c8bc2d91...9203
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
625dc7a31a28...1b97
Settlement height:
700,686
Value:
1.5 ERG
#22
e0a817f7ef07...c93c
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
5a540b119a6e...6d21
Settlement height:
700,686
Value:
5.71 ERG
#23
0166d4564e88...b3bc
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
819e040aeded...51fd
Settlement height:
700,686
Value:
1.38 ERG
#24
a517ee02d074...f193
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
501e2ba50ca7...f370
Settlement height:
700,686
Value:
0.961 ERG
#25
a94aa67b2132...f335
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
bd8be8e99f0e...f6ae
Settlement height:
700,686
Value:
8.31 ERG
#26
254d62626751...0312
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
84d07ff6e549...6b54
Settlement height:
700,686
Value:
1.74 ERG
#27
c6c550a441c7...43f3
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
404b172db66c...6773
Settlement height:
700,686
Value:
2.54 ERG
#28
ecae0e427f45...7220
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
c22973bd88c0...1ae9
Settlement height:
700,686
Value:
2.04 ERG
#29
a435da38fff2...2076
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
ef67127e7069...f3d5
Settlement height:
700,686
Value:
0.145 ERG
Transaction Details
Status: Confirmed
Size: 44.58 KB
Received time: 3/7/2022 05:06:33 AM
Included in blocks: 700,686
Confirmations: 1,056,661
Total coins transferred: 66.47 ERG
Fees: 0.145 ERG
Fees per byte: 0.000003177 ERG
Raw Transaction Data
{
  "id": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
  "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
  "inclusionHeight": 700686,
  "timestamp": 1646629593244,
  "index": 2,
  "globalIndex": 2759233,
  "numConfirmations": 1056661,
  "inputs": [
    {
      "boxId": "0d6b8a7bbacc8483b995c8aa0e89cf89cb66151ed46d5c4cf9817d8551b9a145",
      "value": 2973000000,
      "index": 0,
      "spendingProof": "9e8089b385aedd715aaaced49b38a0fb95e9e67f6a654ef8ff6f31771d962ecd3fa8c71dd51e559bfc56a72096b2df085ca0177b02ba7a2e",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 0,
      "outputGlobalIndex": 13986196,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "bbab92220c0f58730279dcc8bb7044467063859d853b190ecd9bace7c92b4375",
      "value": 1174000000,
      "index": 1,
      "spendingProof": "beb9e87e6aaf23f1de0d64a3d0ea756df005885b4fed6bc07897c8eec3ee4dc4445a8d6a9e123baae92cbebf69f261976cb27e676a5cd731",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 1,
      "outputGlobalIndex": 13986197,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "bd48e75e3ad3e35930a2be0023efae4aa6357788daa97af659ab00c5c223c857",
      "value": 5897000000,
      "index": 2,
      "spendingProof": "b7d3ce610c83802bd9c224846908176707dab3e22ef21ce09a026a6fa53cc10d450587e167a5b32b3940406aef724b17e1c0709c4ddad130",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 2,
      "outputGlobalIndex": 13986198,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "eb68c16c30db6de0c25d78451bf99d9e535d811e660864edfc083ebaf3ce65bd",
      "value": 219000000,
      "index": 3,
      "spendingProof": "63d96a8087a01b33f6bf874ea2a7258142a4bb0b87a6ee6f9a7efbad9b9c7660a47429fa9747d41aea0b13a956c51a5b66fd1ff40cce3448",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 3,
      "outputGlobalIndex": 13986199,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "c2955bad85c37bf8db9a53cdaca5db4ca122ebd8e6b61ca9b3d91a7b96d2f281",
      "value": 2090000000,
      "index": 4,
      "spendingProof": "9e05890bacc1668c6df9926a1e61ec04f8006d7a43070d4c164cd00dc51f2d006d828dc0193aaaccbb7fb988248820bdf5d9cdb8fd3c49f6",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 4,
      "outputGlobalIndex": 13986200,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "cb7f156131dd280316f55dadced2c1585c1d3c8f2e3e22e9b8b01d4284818690",
      "value": 908000000,
      "index": 5,
      "spendingProof": "19e9f279f1a0ad1dfeb9dcef7d24857e7d11b68e4dcdd0e6785fdc8671d66cac489288c78ad9c86bfcee781de3015043e1e9c8db27c2eed7",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 5,
      "outputGlobalIndex": 13986201,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "bebb5101ca383f2912196b3f586138372b3236e90d9df7a12b2109bc155b3cfd",
      "value": 78000000,
      "index": 6,
      "spendingProof": "890806ab43e636e122a452ba79b82ff6f35add5e68569359666de46706f5d75b51f4427280fab1c71466d2015647bb76c4d6494bf7444c4d",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 6,
      "outputGlobalIndex": 13986202,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
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      "spendingProof": "e0576114393e3186aaf13c84088e31854bac54b0b3bd0220a18ca095b6c56bee161d249c9f422f023369f500e1c152003d012d0535cc4586",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 25,
      "outputGlobalIndex": 13986221,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "b682277295cc63e4b0ef12c235dc48e5fda5424a7fcd3598e439b53d5d4eadb3",
      "value": 1743000000,
      "index": 26,
      "spendingProof": "c00fec4145d3f2bf3d5789d6e2e8fda7e37ac47661146993c9dba8b8ff86a2671fe27979832c453774f72e60d6238c400d368119a1247ef0",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 26,
      "outputGlobalIndex": 13986222,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "20de342cb8551a071990ba1388cbe4c139110dfc8623ff2ba238aea3829b03c5",
      "value": 2546000000,
      "index": 27,
      "spendingProof": "fcb1686a55778393317a1b06cf236511ea0267d54ae10b0fe409e8090c9e998b99eac45e8aad933efaae54d10ad904f651795d3ac3f92bbd",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 27,
      "outputGlobalIndex": 13986223,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "45c86c452f0e6013739a65cdbbf0a66882f2d9a4188ea8a6a12f253516445175",
      "value": 2045000000,
      "index": 28,
      "spendingProof": "8f8f918231abc566417f32b0cd3fc54bacb1acf475d80aa82d6ac20aa6bb7eb90cc485638d1d21a13f9d88ad853e75bb564b121ca93a9bbe",
      "outputBlockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "outputTransactionId": "c288d6a65a599cc2bee3e534f19a96e8819cf39ff470d264f563f348960e389a",
      "outputIndex": 28,
      "outputGlobalIndex": 13986224,
      "outputCreatedAt": 700682,
      "outputSettledAt": 700686,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [],
  "outputs": [
    {
      "boxId": "9a986d6c5e342421e9e8660418e5e9066dcfa9374b91cc3805f023074d562c11",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 2968000000,
      "index": 0,
      "globalIndex": 13986227,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "103604000e20c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c004020400010104020101010004020500040404020500040405d00f0580897a040404020500040404000580897a050004000580897a0400040204000404040104040401050001000401040105000100040105000400040101000101050001010400050004000400040001000ec204101c0400040204000402010001000400040101000402010004000402040005020402040404040500040004000400040004000400010001000101d809d601c6a70711d602c6a7080c3c0e0ed60396830601e6c6a7040c3c0e11e6c6a7050c3c0e0ee6c6a7060c4c0ee67201e6720293b2a4730000a7d604b2a4730100d605c67204050c3c0e0ed606c67204040c3c0e11d607b2a5730200d608c672070711d609db63087207957203d195ed9595957203aee47202d9010a3c0e0e938c720a01c2b2a4730300730496830501e6c67204040c3c0e11e6c67204050c3c0e0ee6c67204060c4c0ee6c672040711e6c67204080c3c0e0e7305afe47205d9010a3c0e0e94dc0c1aade47206d9010c3c0e118c720c01028c720a01730673077308959593c27207c2a796830701e6c67207040c3c0e11e6c67207050c3c0e0ee6c67207060c4c0ee6c672070711e6c67207080c3c0e0e93c17207c1a793b1db630872077309730ad804d60ae47208d60be47201d60cb2720b730b00d60db2720a730c00ededed93b2720a730d009a720c730eed90720d7ea30591720db2720b730f0093b2720a731000b2720b7311009594720c7312938cb2db6308a7731300018cb2720973140001d801d60edb6308a79591b1720e7315938cb2720e731600018cb2720973170001938cb2720973180001c5a773199683050193e4c67207040c3c0e11e4720693e4c67207050c3c0e0ee4720593e4c67207060c4c0ee4c67204060c4c0e93e47208e4c67204071193e4c67207080c3c0e0ee4c67204080c3c0e0e731ad1731b0101d805d601c2a7d602b5a4d901026393c272027201d603b17202d604b2a4730000d605730195ef95ed917203730293c5b27202730300c5a7730495937203730573067307d1dad9010601957206d807d608e4c6b2a4730800040c3c0e11d609e4c67204040c3c0e11d60a99b072027309d9010a41639a8c720a01c18c720a02b0b57209d9010a3c0e11d801d60c8c720a028fb2720c730a00b2720c730b00730cd9010a413c0e119a8c720a01b28c8c720a0202730d00d60bade4c67204060c4c0ed9010b4c0ed801d60d9d9c7e8c720b0205720a730e86028c720b0199720d9e720d730fd60cada5d9010c63c2720cd60dada5d9010d63c1720dd60eb0b57208d9010e3c0e11d801d6108c720e028fb27210731000b272107311007312d9010e413c0e119a8c720e01b28c8c720e0202731300edededaf7208d9010f3c0e11d807d6118c720f01d612dc0c1aad7209d901123c0e118c7212010272117314d6138c720f02d614dad9011405d801d6169d9c99b0720b720ad90116414d0e998c7216018c8c721602029c73157eb17208057214b072087316d90116413c0e119a8c721601b28c8c721602027317009972169e7216731801b27213731900d615b27213731a00d616dc0c1a720c027211731bd617b27213731c0095947212731dd801d6189ab2b2ad7209d901183c0e118c721802721200731e00721495927218721595947216731fed93b2720d721600721893721773207321ed93721673229372177218959272147215959472167323ed93b2720d721600721493721773247325ed93721673269372177214af720bd9010f4d0ed801d6118c720f02959172117327d801d612dc0c1a720c028c720f01732895947212732993c1b2a57212007211732a732b9591720e732caea5d9010f63ed93c1720f720e93c2720f7201732d9594b2e4c672040711732e00732f938cb2db63087204733000017205d801d60fdb630872049591b1720f7331938cb2720f73320001720593c57204720573330193c272047334d17335",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "11ffc4f81f55ce14f31c7e104b3c8a2ba6d68650f596acddbb0ff87273d952da",
      "mainChain": true
    },
    {
      "boxId": "b58120684fd4c74a92cd8be6f52f35c8207baebee610fdad9d51be71549c1e02",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 1169000000,
      "index": 1,
      "globalIndex": 13986228,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "e0876dff03792783e814ff9e062a85e7a02b1f8546594efaa5ddd9212e6dcfa4",
      "mainChain": true
    },
    {
      "boxId": "ac04eea316fbb0266f2c0e7630bce933d63f4a7f6061240f286745d8c46602ba",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 5892000000,
      "index": 2,
      "globalIndex": 13986229,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "975756a308e86f54554a0bd6e6e56a5327d443d5ebbe066e80537f6ea1f6866f",
      "mainChain": true
    },
    {
      "boxId": "1af7421de9c74ba756e497631646cfb08d17f788687faa26915f522f7027e89c",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 214000000,
      "index": 3,
      "globalIndex": 13986230,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "103604000e20c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c004020400010104020101010004020500040404020500040405d00f0580897a040404020500040404000580897a050004000580897a0400040204000404040104040401050001000401040105000100040105000400040101000101050001010400050004000400040001000ec204101c0400040204000402010001000400040101000402010004000402040005020402040404040500040004000400040004000400010001000101d809d601c6a70711d602c6a7080c3c0e0ed60396830601e6c6a7040c3c0e11e6c6a7050c3c0e0ee6c6a7060c4c0ee67201e6720293b2a4730000a7d604b2a4730100d605c67204050c3c0e0ed606c67204040c3c0e11d607b2a5730200d608c672070711d609db63087207957203d195ed9595957203aee47202d9010a3c0e0e938c720a01c2b2a4730300730496830501e6c67204040c3c0e11e6c67204050c3c0e0ee6c67204060c4c0ee6c672040711e6c67204080c3c0e0e7305afe47205d9010a3c0e0e94dc0c1aade47206d9010c3c0e118c720c01028c720a01730673077308959593c27207c2a796830701e6c67207040c3c0e11e6c67207050c3c0e0ee6c67207060c4c0ee6c672070711e6c67207080c3c0e0e93c17207c1a793b1db630872077309730ad804d60ae47208d60be47201d60cb2720b730b00d60db2720a730c00ededed93b2720a730d009a720c730eed90720d7ea30591720db2720b730f0093b2720a731000b2720b7311009594720c7312938cb2db6308a7731300018cb2720973140001d801d60edb6308a79591b1720e7315938cb2720e731600018cb2720973170001938cb2720973180001c5a773199683050193e4c67207040c3c0e11e4720693e4c67207050c3c0e0ee4720593e4c67207060c4c0ee4c67204060c4c0e93e47208e4c67204071193e4c67207080c3c0e0ee4c67204080c3c0e0e731ad1731b0101d805d601c2a7d602b5a4d901026393c272027201d603b17202d604b2a4730000d605730195ef95ed917203730293c5b27202730300c5a7730495937203730573067307d1dad9010601957206d807d608e4c6b2a4730800040c3c0e11d609e4c67204040c3c0e11d60a99b072027309d9010a41639a8c720a01c18c720a02b0b57209d9010a3c0e11d801d60c8c720a028fb2720c730a00b2720c730b00730cd9010a413c0e119a8c720a01b28c8c720a0202730d00d60bade4c67204060c4c0ed9010b4c0ed801d60d9d9c7e8c720b0205720a730e86028c720b0199720d9e720d730fd60cada5d9010c63c2720cd60dada5d9010d63c1720dd60eb0b57208d9010e3c0e11d801d6108c720e028fb27210731000b272107311007312d9010e413c0e119a8c720e01b28c8c720e0202731300edededaf7208d9010f3c0e11d807d6118c720f01d612dc0c1aad7209d901123c0e118c7212010272117314d6138c720f02d614dad9011405d801d6169d9c99b0720b720ad90116414d0e998c7216018c8c721602029c73157eb17208057214b072087316d90116413c0e119a8c721601b28c8c721602027317009972169e7216731801b27213731900d615b27213731a00d616dc0c1a720c027211731bd617b27213731c0095947212731dd801d6189ab2b2ad7209d901183c0e118c721802721200731e00721495927218721595947216731fed93b2720d721600721893721773207321ed93721673229372177218959272147215959472167323ed93b2720d721600721493721773247325ed93721673269372177214af720bd9010f4d0ed801d6118c720f02959172117327d801d612dc0c1a720c028c720f01732895947212732993c1b2a57212007211732a732b9591720e732caea5d9010f63ed93c1720f720e93c2720f7201732d9594b2e4c672040711732e00732f938cb2db63087204733000017205d801d60fdb630872049591b1720f7331938cb2720f73320001720593c57204720573330193c272047334d17335",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "078d851d8000c6676ec0d0af5e2346a99da9206a189b895fa74db8f854714250",
      "mainChain": true
    },
    {
      "boxId": "641653c93f96d1b23fbbccf7294f654ba42f92e85c6b8d4f53baa9fb16817055",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 2085000000,
      "index": 4,
      "globalIndex": 13986231,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "105aa81854f17e6f0a8f187352dddabe705594fd43034cb0d37e2dbb73a70163",
      "mainChain": true
    },
    {
      "boxId": "6759b29577f380e7b50ebabfee0ef8c5e9af49c62195732381ed067775720e45",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 903000000,
      "index": 5,
      "globalIndex": 13986232,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "f3a5f5c9163c8f2ff0dd3f1229dfb658745b9094a6b53a340f6a194caa8f758f",
      "mainChain": true
    },
    {
      "boxId": "f18869b3486555e668358043865b3feb67b33b1bd2f9411c4860149f422a9436",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 73000000,
      "index": 6,
      "globalIndex": 13986233,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "3b181328274539f8e72a9d696eb6715e7451f76718dd25411ef3271e9d3b8057",
      "mainChain": true
    },
    {
      "boxId": "cf246a1084c53c3e4070a817261cd203c8fb42674db230836d6644a88f241a86",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 756000000,
      "index": 7,
      "globalIndex": 13986234,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "5c7ee8f2ac49ca0ffd22151afa067d9cf4815fb0c260169aa0cec7f2f239b0a7",
      "mainChain": true
    },
    {
      "boxId": "fea1b6b69bda0dc997a747bf9e6924a7e86f62a27eae5a18fa97a322d57d9cbb",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 2506000000,
      "index": 8,
      "globalIndex": 13986235,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "103604000e20c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c004020400010104020101010004020500040404020500040405d00f0580897a040404020500040404000580897a050004000580897a0400040204000404040104040401050001000401040105000100040105000400040101000101050001010400050004000400040001000ec204101c0400040204000402010001000400040101000402010004000402040005020402040404040500040004000400040004000400010001000101d809d601c6a70711d602c6a7080c3c0e0ed60396830601e6c6a7040c3c0e11e6c6a7050c3c0e0ee6c6a7060c4c0ee67201e6720293b2a4730000a7d604b2a4730100d605c67204050c3c0e0ed606c67204040c3c0e11d607b2a5730200d608c672070711d609db63087207957203d195ed9595957203aee47202d9010a3c0e0e938c720a01c2b2a4730300730496830501e6c67204040c3c0e11e6c67204050c3c0e0ee6c67204060c4c0ee6c672040711e6c67204080c3c0e0e7305afe47205d9010a3c0e0e94dc0c1aade47206d9010c3c0e118c720c01028c720a01730673077308959593c27207c2a796830701e6c67207040c3c0e11e6c67207050c3c0e0ee6c67207060c4c0ee6c672070711e6c67207080c3c0e0e93c17207c1a793b1db630872077309730ad804d60ae47208d60be47201d60cb2720b730b00d60db2720a730c00ededed93b2720a730d009a720c730eed90720d7ea30591720db2720b730f0093b2720a731000b2720b7311009594720c7312938cb2db6308a7731300018cb2720973140001d801d60edb6308a79591b1720e7315938cb2720e731600018cb2720973170001938cb2720973180001c5a773199683050193e4c67207040c3c0e11e4720693e4c67207050c3c0e0ee4720593e4c67207060c4c0ee4c67204060c4c0e93e47208e4c67204071193e4c67207080c3c0e0ee4c67204080c3c0e0e731ad1731b0101d805d601c2a7d602b5a4d901026393c272027201d603b17202d604b2a4730000d605730195ef95ed917203730293c5b27202730300c5a7730495937203730573067307d1dad9010601957206d807d608e4c6b2a4730800040c3c0e11d609e4c67204040c3c0e11d60a99b072027309d9010a41639a8c720a01c18c720a02b0b57209d9010a3c0e11d801d60c8c720a028fb2720c730a00b2720c730b00730cd9010a413c0e119a8c720a01b28c8c720a0202730d00d60bade4c67204060c4c0ed9010b4c0ed801d60d9d9c7e8c720b0205720a730e86028c720b0199720d9e720d730fd60cada5d9010c63c2720cd60dada5d9010d63c1720dd60eb0b57208d9010e3c0e11d801d6108c720e028fb27210731000b272107311007312d9010e413c0e119a8c720e01b28c8c720e0202731300edededaf7208d9010f3c0e11d807d6118c720f01d612dc0c1aad7209d901123c0e118c7212010272117314d6138c720f02d614dad9011405d801d6169d9c99b0720b720ad90116414d0e998c7216018c8c721602029c73157eb17208057214b072087316d90116413c0e119a8c721601b28c8c721602027317009972169e7216731801b27213731900d615b27213731a00d616dc0c1a720c027211731bd617b27213731c0095947212731dd801d6189ab2b2ad7209d901183c0e118c721802721200731e00721495927218721595947216731fed93b2720d721600721893721773207321ed93721673229372177218959272147215959472167323ed93b2720d721600721493721773247325ed93721673269372177214af720bd9010f4d0ed801d6118c720f02959172117327d801d612dc0c1a720c028c720f01732895947212732993c1b2a57212007211732a732b9591720e732caea5d9010f63ed93c1720f720e93c2720f7201732d9594b2e4c672040711732e00732f938cb2db63087204733000017205d801d60fdb630872049591b1720f7331938cb2720f73320001720593c57204720573330193c272047334d17335",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "7aee841b14fe8d6ed99e3459d7b7d9c2e3bdfb536e8b895c0f4699b82a43ac90",
      "mainChain": true
    },
    {
      "boxId": "03ad7748035dc10f98585310f8ab363c026c77cb6950fae7f21b4cdc88bab371",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 1457000000,
      "index": 9,
      "globalIndex": 13986236,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "5e508403e8d58f8eff709a857c256ce82f0b34f993eec86caab9f96557ca6aa6",
      "mainChain": true
    },
    {
      "boxId": "4c521c4f9ece6ab85f00dae38001086a7c0e192ed149cea6267cef0bcf9040d2",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 2515000000,
      "index": 10,
      "globalIndex": 13986237,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "a3a60c02aa726fed21f8fb16fb08f462f50f5aa5ed22a63b3bc59ee29ba5664c",
      "mainChain": true
    },
    {
      "boxId": "b8b5181636754b5306d9d3a12c6cc58e665875c2dc8ff261781b4536374bfb44",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 6388000000,
      "index": 11,
      "globalIndex": 13986238,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "b73cdc54de7664d3173512520cf56a034736052886c87a5f1b6776cfb18d7902",
      "mainChain": true
    },
    {
      "boxId": "71f7ad7efa43b18b018349882ce34cbb45d9eeb982c0711833e79f4af5e56b2b",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 714000000,
      "index": 12,
      "globalIndex": 13986239,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "56d27ae170e52d88d4d5e486251a03be481bc29e8895451d1f8002e6f65b9f6d",
      "mainChain": true
    },
    {
      "boxId": "009b9a85cd41e2a12450e5c2765ce6083ea751d06f137e717c77d32f330c5af7",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 2610000000,
      "index": 13,
      "globalIndex": 13986240,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "45df7a86cbbd5a1bfcb9fd9d296dd63755c155948360c12c9794f7bdfa12a989",
      "mainChain": true
    },
    {
      "boxId": "a2bf1b1a53715669371de4ac5926d2a47354193bbc85ba39566f2d14674e794a",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 752000000,
      "index": 14,
      "globalIndex": 13986241,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "e8b941132b9e88b3c60d7cb41abc3edc0841fdd5fd9046fb992035b56118f0c1",
      "mainChain": true
    },
    {
      "boxId": "0e7e2862211f0436e95450fb7c03bf0e503ade177bfe489c0d9a28732401be1d",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 951000000,
      "index": 15,
      "globalIndex": 13986242,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "44efaa38db873ee80f28fbfe010f4480a40e30a1fe877d39af3ccb43ea381d26",
      "mainChain": true
    },
    {
      "boxId": "20ce019d50e86493b3f1403c481ce8fc81dcdd0124864926ada377f83c438d7d",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 1245000000,
      "index": 16,
      "globalIndex": 13986243,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "02abc2cb1cb86faec050e766d033885c35121fe1e81f89336a60dad195914166",
      "mainChain": true
    },
    {
      "boxId": "2db93d8ea6d0694e63190b3b5a522c9b0dc790c380fc7c3918276352f3d831e6",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 1090000000,
      "index": 17,
      "globalIndex": 13986244,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "0e1296486455b34be2b06c985078953a6983712de0633bd99bf827f0ccb958ec",
      "mainChain": true
    },
    {
      "boxId": "9484dd06e7ef64ee783debe00711b4eaca0fc15c5321333a718010ba653997e2",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 3483000000,
      "index": 18,
      "globalIndex": 13986245,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "47d1bf30da9aaeafe9f97243e862cb1363b8cee1cdc14055e2ec0171dd80b2a8",
      "mainChain": true
    },
    {
      "boxId": "e9ba5da9b50d890502f97af5ec3371b361121d6355742ad4b35a3be213881d90",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 289000000,
      "index": 19,
      "globalIndex": 13986246,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "0595e171b77d0cb1abff8301296f4c5ffff3fca1a2e503bfbfd0e582d5562f6e",
      "mainChain": true
    },
    {
      "boxId": "1b6e092b0ce2f94a4bf79354ef4aaee6209ae99d456253ae6a32f6faaf30c854",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 4082000000,
      "index": 20,
      "globalIndex": 13986247,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "3d33c930bf40dd9062300fb60446567c3cb5363f7e7009233b0909e3b7e416e5",
      "mainChain": true
    },
    {
      "boxId": "a9a4c8bc2d913720f97d3af2cabaf92a2d88e59871c399f42282c4f46fda9203",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 1502000000,
      "index": 21,
      "globalIndex": 13986248,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "625dc7a31a28fb25007dbb5c1d03725a71320120b483153d48389c1dc5fd1b97",
      "mainChain": true
    },
    {
      "boxId": "e0a817f7ef07dc9e83a8f8e6511b8c245753d6ecc87ae221bb77e1536981c93c",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 5709000000,
      "index": 22,
      "globalIndex": 13986249,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "5a540b119a6ecb4cd2534d89e0fece5e20cc7771c02de52d70ed95d797576d21",
      "mainChain": true
    },
    {
      "boxId": "0166d4564e885e18330ff14f0859dc36acee3be0f424a1d9418b82bf7659b3bc",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 1384000000,
      "index": 23,
      "globalIndex": 13986250,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "819e040aeded87f9abac3b13711a700a90c7c469f66a479461cf433f5c4251fd",
      "mainChain": true
    },
    {
      "boxId": "a517ee02d074fa1fbb14c72da82d314b29404d25d96aca5d66e8af2547f0f193",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 961000000,
      "index": 24,
      "globalIndex": 13986251,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "501e2ba50ca74f26bdb432e5036b04f9eabde11246e7228bae9c6e9b043af370",
      "mainChain": true
    },
    {
      "boxId": "a94aa67b2132d61943c43f5f27dcf3195e49fff676cba9ff974a3a71e440f335",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 8307000000,
      "index": 25,
      "globalIndex": 13986252,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "bd8be8e99f0e4823370424b845a3233dfdd99d94f2e09e38758f60378cfef6ae",
      "mainChain": true
    },
    {
      "boxId": "254d62626751677df24c2759054e05558c8b8a8e6fbbb3419ef43ce605610312",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 1738000000,
      "index": 26,
      "globalIndex": 13986253,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "84d07ff6e549b070ae51d8be3b902918072275de385c28112b544dd3f0a26b54",
      "mainChain": true
    },
    {
      "boxId": "c6c550a441c7e62f54ab986f043f50accc78374024f3c8be9a7487eade7143f3",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 2541000000,
      "index": 27,
      "globalIndex": 13986254,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "404b172db66cb54c0e2df8be1d3d07cef1f64b6dd207832326f2f9daf6a06773",
      "mainChain": true
    },
    {
      "boxId": "ecae0e427f452092abcaba35cfa349500f0f20ca1c231e94a5731ee824327220",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 2040000000,
      "index": 28,
      "globalIndex": 13986255,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n  val i3 = coll2.size\n  val box4 = INPUTS(placeholder[Int](0))\n  val coll5 = placeholder[Coll[Byte]](1)\n  if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n    if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n  }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n          val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n          val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n              val coll12 = tuple10._2\n              coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n            }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n          val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n              val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n              (tuple11._1, l13 - l13 % placeholder[Long](15))\n            })\n          val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n          val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n          val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n              val coll16 = tuple14._2\n              coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n            }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n          ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n                  val coll17 = tuple15._1\n                  val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n                  val coll19 = tuple15._2\n                  val l20 = {(l20: Long) =>\n                    val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n                    l22 - l22 % placeholder[Long](24)\n                  }(coll19(placeholder[Int](25)))\n                  val l21 = coll19(placeholder[Int](26))\n                  val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n                  val l23 = coll19(placeholder[Int](28))\n                  if (i18 != placeholder[Int](29)) {(\n                    val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n                    if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n                  )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n                }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n                  val l17 = tuple15._2\n                  if (l17 > placeholder[Long](39)) {(\n                    val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n                    if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n                  )} else { placeholder[Boolean](43) }\n                })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n            val coll15 = box4.tokens\n            if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n          )}\n        )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "c22973bd88c0f980474be80ca806fadc22b788e66f2b74b34f5dd9406c351ae9",
      "mainChain": true
    },
    {
      "boxId": "a435da38fff282a27dea241998a26fb52a8c48e807137c6c77f16274706c2076",
      "transactionId": "80fb55586d03fa273e27edbe6b237fc3d6ffc76a138aaac07bcd879bf64b395d",
      "blockId": "7e6046ec0d716ed0504f0bf23f2a565404108df1fd481384bf69aec9dc5105d9",
      "value": 145000000,
      "index": 29,
      "globalIndex": 13986256,
      "creationHeight": 700682,
      "settlementHeight": 700686,
      "ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
      "ergoTreeScript": "{sigmaProp(\n  allOf(\n    Coll[Boolean](\n      HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n        placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n      ), OUTPUTS.size == placeholder[Int](4)\n    )\n  )\n)}",
      "address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "ef67127e7069539a0a7cbadd16e6114c700ccd066c14ff8815490d283640f3d5",
      "mainChain": true
    }
  ],
  "size": 45646,
  "isUnconfirmed": false
}