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Transaction

3/14/2022 10:51:35 AM
ID: e6a4b0c65c...0869
Inputs (29)
#0
a8bf8986a1a5...bbed
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
1.68 ERG
#1
acae53d370d4...da6e
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
2.01 ERG
#2
bda8fb4a54f0...fee1
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
2.45 ERG
#3
25ecfb0e0117...b664
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.183 ERG
#4
acfa45b81a4f...9ac1
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
2.42 ERG
#5
27eb4ef9897c...b4bc
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
2.77 ERG
#6
8b358f5e6451...f769
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
3.85 ERG
#7
735a3b761d3b...c776
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.677 ERG
#8
072670fd9829...18ea
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
8.24 ERG
#9
7ecd2dd1367c...4089
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
2.25 ERG
#10
a5f70f919c58...660b
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.172 ERG
#11
4c1eeade2693...78e8
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.084 ERG
#12
cdc3d093973a...b228
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
4.53 ERG
#13
2a83a3ab8706...7ab9
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
1.83 ERG
#14
3dca72f15b53...a219
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
2.62 ERG
#15
2b9cee81b731...16f4
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.871 ERG
#16
df3b0f9fcaff...859d
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
1.65 ERG
#17
bfdd5087a96d...204b
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
1.21 ERG
#18
0f05d771e316...f19a
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
4.41 ERG
#19
ab64b0dbac62...940c
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.883 ERG
#20
682b853350a3...11ea
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
1.2 ERG
#21
333f6728fde2...59f9
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.249 ERG
#22
cebaaa79f55e...5f20
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
9.67 ERG
#23
78b68a7ace0e...74d8
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
3.32 ERG
#24
de0096b6dddb...0187
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
1.24 ERG
#25
6961c327ab10...ea29
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.507 ERG
#26
67d8eed3868e...c996
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
4.59 ERG
#27
a8e355db4160...c710
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.39 ERG
#28
d280abc782c2...899e
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
3624396a88fe...60b6
Settlement height:
706,004
Value:
0.704 ERG
Outputs (30)
#0
7a0a86977a93...85a5
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
931884c76628...201e
Settlement height:
706,004
Value:
1.68 ERG
#1
45bf2f492bfb...d33a
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
6038c5e2264d...9575
Settlement height:
706,004
Value:
2.01 ERG
#2
bedc11b4e800...a870
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
304c149f50f2...e311
Settlement height:
706,004
Value:
2.44 ERG
#3
0d00a3b4cfe6...eb79
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
bb115bbb7abb...a5e4
Settlement height:
706,004
Value:
0.178 ERG
#4
d316f4fee494...ab34
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
fec00e967b30...decb
Settlement height:
706,004
Value:
2.42 ERG
#5
383fe109030c...a019
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
52816d59b141...e7ec
Settlement height:
706,004
Value:
2.76 ERG
#6
84cd257cce88...a337
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
1bb36bd1767f...1a70
Settlement height:
706,004
Value:
3.84 ERG
#7
e6e527f5c128...4523
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
e9aa0243c2a7...5f8f
Settlement height:
706,004
Value:
0.672 ERG
#8
db1166a31b84...690e
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
9207bc0be545...caff
Settlement height:
706,004
Value:
8.23 ERG
#9
1e238c76d9d9...cb15
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
9635a470ce88...bdd0
Settlement height:
706,004
Value:
2.24 ERG
#10
315436a8d631...934b
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
761cee1b572a...7d67
Settlement height:
706,004
Value:
0.167 ERG
#11
8e79ad312306...d4ee
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
e6cab0028132...0338
Settlement height:
706,004
Value:
0.079 ERG
#12
08c8aa8c6cba...23f3
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
6b776fac5f9b...a6a8
Settlement height:
706,004
Value:
4.52 ERG
#13
a78da7434369...7083
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
8402cfd91f6d...d48e
Settlement height:
706,004
Value:
1.82 ERG
#14
50ac6d8d9a61...09f3
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
e95a6f3035b5...1b0c
Settlement height:
706,004
Value:
2.61 ERG
#15
d3917e53f903...8c3e
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
4a721235ead7...a84d
Settlement height:
706,004
Value:
0.866 ERG
#16
bbd5f595a7f0...7d14
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
5b9d9c3120b4...f492
Settlement height:
706,004
Value:
1.65 ERG
#17
7ad3ac86d350...a6a6
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
18e531710930...4e99
Settlement height:
706,004
Value:
1.21 ERG
#18
090082b78d98...ebf5
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
e9f3c5caef68...bead
Settlement height:
706,004
Value:
4.4 ERG
#19
74e265396570...646e
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
1f573e4884a1...765d
Settlement height:
706,004
Value:
0.878 ERG
#20
f189d011e5f9...2992
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
4cb29788e8ff...d911
Settlement height:
706,004
Value:
1.19 ERG
#21
761a4dec4bbe...4621
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
359b70af8025...2149
Settlement height:
706,004
Value:
0.244 ERG
#22
46e08e4f649d...de8d
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
888a32f32453...bc99
Settlement height:
706,004
Value:
9.66 ERG
#23
da0cffb9f8ac...4d48
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
545751ad6169...1c76
Settlement height:
706,004
Value:
3.32 ERG
#24
5704d816dd64...2155
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
4fa95cc54641...39d8
Settlement height:
706,004
Value:
1.24 ERG
#25
b46670cb1644...53a2
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
3e4aa83fb1b5...3bf4
Settlement height:
706,004
Value:
0.502 ERG
#26
aa9a32650ff9...f382
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
b39c5d63b9a2...4a66
Settlement height:
706,004
Value:
4.59 ERG
#27
bb27c22e0043...07ad
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
f5a2babe5173...9e21
Settlement height:
706,004
Value:
0.385 ERG
#28
7047a89d85b7...028c
Spent
Address:
3pyaMZRJbtRc...XVdo
Spent in transaction:
e5f46c4c8807...65ea
Settlement height:
706,004
Value:
0.699 ERG
#29
e81427c148bf...ce81
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
a50a2474e5d6...6219
Settlement height:
706,004
Value:
0.145 ERG
Transaction Details
Status: Confirmed
Size: 44.57 KB
Received time: 3/14/2022 10:51:35 AM
Included in blocks: 706,004
Confirmations: 1,062,338
Total coins transferred: 66.64 ERG
Fees: 0.145 ERG
Fees per byte: 0.000003177 ERG
Raw Transaction Data
{
  "id": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
  "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
  "inclusionHeight": 706004,
  "timestamp": 1647255095195,
  "index": 3,
  "globalIndex": 2798484,
  "numConfirmations": 1062338,
  "inputs": [
    {
      "boxId": "a8bf8986a1a5159e4e811a9cf12852b0f38924886c1e28256ac4d25c5d8dbbed",
      "value": 1683000000,
      "index": 0,
      "spendingProof": "d37729c904754644617088a5b79217adf475e0ea545ff61cf9808fcad6b8e595450ff4ec4eaa7b4bb113f0a2f511ae139e2f5617ab2d05c4",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 0,
      "outputGlobalIndex": 14256254,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "acae53d370d4f19dcc2753b236f4cd57082d0c9adcef3478c8df4c3dc8c8da6e",
      "value": 2011000000,
      "index": 1,
      "spendingProof": "e1d81187ddc87249534613e01c3d0b17fdd12b7b8d530112541d1b1566062a46efa9c3b4935eba9c5392d9ba593a4a3eae6a0716005558a2",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 1,
      "outputGlobalIndex": 14256255,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "bda8fb4a54f0e27ab0d09dbfe68feaae92450024adeb6743fe4e31645375fee1",
      "value": 2448000000,
      "index": 2,
      "spendingProof": "1084c34f68120e1cbb3397b5a65802e8828615128ef5b11237f9fc5ab2e291a614c36a9e70b572619426e07dd65edb23c582358d01f738c6",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 2,
      "outputGlobalIndex": 14256256,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "25ecfb0e0117100a54b3d415003b22d3b1a1667abc2711358020c5fb2975b664",
      "value": 183000000,
      "index": 3,
      "spendingProof": "25355dc0bbf71f4cf3ddfebe90e11afeb523db92bf6e79ce8bf5e487be757ab69db7b18d758c6ff3c99c22ce8cfab15920d1b25f0c48e528",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 3,
      "outputGlobalIndex": 14256257,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "acfa45b81a4f04d3267466f60e489521945865d78c69ba1a68598d42f1729ac1",
      "value": 2422000000,
      "index": 4,
      "spendingProof": "15a71fc6668e000072ad87fd295d80c9212d7b5819d30a1638cc146598190219e44e59cb215b084f697c9e0d30072ed5f08f5379ddc56b47",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 4,
      "outputGlobalIndex": 14256258,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "27eb4ef9897c9970033cd08e8dd1b4b8c766c7b92462897c346d8755ac09b4bc",
      "value": 2768000000,
      "index": 5,
      "spendingProof": "2ccc1db3bbf31e1e8ca362f21b38602418dd7b8af5edb3f7a2a84c0aadd74c44d0884efbe181e52670ac845dff19488bbcc8a545c596ddb7",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 5,
      "outputGlobalIndex": 14256259,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "8b358f5e645170613d29d2d7d914a006dc6f76424e71d64c13ff9497ac90f769",
      "value": 3847000000,
      "index": 6,
      "spendingProof": "8d7733db0a0f475ecfeb2256ecaaeedc630eaf721e4834870f79bf8cf2fa60d2f2fc1465bfe0c8e2d7a176ebb69b54aeec80765b1b5c5025",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 6,
      "outputGlobalIndex": 14256260,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
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      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 25,
      "outputGlobalIndex": 14256279,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "67d8eed3868e71e97236a9345e6406a37ea7c92d66921c8acd4d8f4bbcedc996",
      "value": 4591000000,
      "index": 26,
      "spendingProof": "00bc8fb66e4e0f0831c51d11ae20bac5e4ee8b2aba6c7e0c4e45060bc6eac188001e321df695b3e825622dd6374c422f0e2c88896aaea9ae",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 26,
      "outputGlobalIndex": 14256280,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "a8e355db416033ccfb9f8b8505561c398d5317a26a98743e503b16e65f1ac710",
      "value": 390000000,
      "index": 27,
      "spendingProof": "ab599dc225164d70c274ab6b423fba7e87e7f64013fda805ff9e86fd963aeff59f029d110faf806f476249b661cfaf97afcc4783eaabd8e0",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 27,
      "outputGlobalIndex": 14256281,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "d280abc782c295d70bade3894fa8c97e4df1259e37ab351da158e9ba7959899e",
      "value": 704000000,
      "index": 28,
      "spendingProof": "3aea8b73e50120c8752793620f08758d13330dcd4070068820141753c6aa270a8bb226acb53bac7f641911fcf40fceffc85a890176787b88",
      "outputBlockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "outputTransactionId": "3624396a88fe584638bf795aa1f8b35ba2244b91282a676e3237ba9bbb6460b6",
      "outputIndex": 28,
      "outputGlobalIndex": 14256282,
      "outputCreatedAt": 706001,
      "outputSettledAt": 706004,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [],
  "outputs": [
    {
      "boxId": "7a0a86977a9324443a0e2437500cfbcd76530c40f1ea350d3b9b32ae946a85a5",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 1678000000,
      "index": 0,
      "globalIndex": 14256288,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "3pyaMZRJbtRcrho2Dnde59dgo6mbNVv54wCHz1AVevssnztHgKEA8Xrz8TSBiuE4jK39UW68KEM24pBEz49U84MUHbHMvh8eDJeBCpd5C45u9k3ngggNx2DavrVLnhpKmi6yw9RQZpCRSV3BzyHY3RCbSG6tgMAShTbGnWfbbMPsFkTmG4D7qoxqeDfaqg2Ge2DErMMeS7Hq8EtnU6SxLNqFPvuzAH2AiLcAVVgNBd5pNNvDmEuCqjnnASWoame3La4cToxNpph5fUtpbVfjNCVdWaZP3ShLUZcoZvkYg4ngGVH9jLpTYSUTPvtURKRoTsmGPCtf4kDcbz1U7H7c1niYPztcxUkUPtSTsRddQ6nSUYpMev4YgkYAUd7XteETqw6UqJWEcRpiXacypFggHEKWkpWjNG6U8vmjqrdj8L6zxp8Ryi39vVSc8vPMSsXeqSLiogG8SdvFcp1AFe6eQt4htjcikWt1bgfDNdZ8XkLonKXs9E35CzykN2EpBqcDYKiEMAMPQjFT326cdWMg6bwmuZeaz6yzY1H3iH3vfyph6uGBcVVszFUmL9YrGtv7b1Kdrwe9idYaBcz22YPx6PFN4Pv3ts9Ss5s74M9xSPWYPynf6GV5zoEzihuHE6ty64YX4XmuAWEC2k2T83vnkFXbiSMEMC5q9294DEu1V6vosHyKVpSnvYiHzPKtk7eP7S1CGUCeJeNGAikKLdf2sH7UVd23TGb9YGaRCGTotzdUBD3mwGTd12g8dF9whGkwvNNJdZcLVNqwbnVyaKacJFwmGbT3dS9Lp7WS6wUJpoUocFW1CmE8Z31yrJtbEuAejuWMG4YFHpjPjm9y6rZ9ZERevdSQRCwdjshv9VR4WqwLrzfRNAjePedUUJ9K6Dhwn71wtCm9U9LcTzKt9htCUdXzYiG8GLEbST7K6CzVMuhfgo8qDxCz7V6esN3m3muYwx3EtngwoXCPsyWaYToLRZvMPqRxBryZdz11jvtPvVCpnuk8hTnp2yJSLSRPEyoaKUyiEu4qB31B5V9qpGs2MVPovTpRAVLcipxhsSRdMXYvXuat1FaPUthRQyKtbxiHg9aXJivvQAvCPgNLZrHuHudUiwGSvaDWgdPJ4KzYK5DyiD2ENZX2NyWU1ZWCu4vMTJudSKYHefVSu3yXeLR8TsLP6k2ackrM4wYBTLkiZQyxTeKCFzMyPSShgPxjM3EFeXC5vyNqfHDgogHPrGJp8tPdGkS6hTdV2CAJj4SDkzWTsgwrTiY6uHunR3DSg8Yvh4BPtq9hTGtpQuak5vv1h1x6Yma6JtyVBdyqHnj4aACFt4bYxJGKMmekJA7Lmx8JgrgVoT6qvFNNpGGqAmuaVXBZp2rPAXiAmSHuoXNakEzb1XCqCyq2s55QhNDmPNCfQBB9CUWC5vZZZyA2CjaWxsJb2GDXPvCPgQRhBtqUzCu1EGjytPkbgkKjFQgfBqQZboYCVGWP3PxDj2QMsuFAHWdpFR9LBDNAnPRPYYCyHJ7PwRcg19WZxxMeGtsZaPV2hM3NDWsY2wH149JyXfb3jEM8S84oeADQQSuVZz1wzJrVGvWQJRCvzTVBrCpxv8c3emvA9kWZWCMYRExShPDpsDnCqo1TGdndtiY9NvPcxgGX8F6sWAkhg67D4hv94fW5VUQ7PtVdUyKaLA7o9q1GgNN41k7AgwRBGMMMJZA3hto5URSCgwj6wsv7rhBnbe9ze1TJc66EBsyeZUS58TXbtsT8cLAfHtZTyVzCsBxRhLJqsYr67ASdGvHwdSvEpf1xNwB9yKGEYZhU97YZUxV6aqaGHkUHr6iWpuQn3LCrEz5ZJMusj38YK8nkvQ78z3CJfTUAysty2RvTSBKr6U32hAX2vGthsiLxPgMPmc1sD6f72tjuq9NocCoLYf6vN2H74BTB8GXbQCQ7AbEVct8GryNdgG4HHkmRMUdbTCc2iKgZ2obicR3jfygHguaWUBvZVeZp64f2cTRihfdKhGMux1baUFXVdo",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "931884c76628231c706316d4ed6c37a8977a6f96d19cc42cb448c498e581201e",
      "mainChain": true
    },
    {
      "boxId": "45bf2f492bfba5ee41c504a71728ecbe1ce48786474b1513853c8bddfe46d33a",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 2006000000,
      "index": 1,
      "globalIndex": 14256289,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "6038c5e2264d93df6f0ae867accca368e0b43e366a5036e234d85cbdc2379575",
      "mainChain": true
    },
    {
      "boxId": "bedc11b4e8000612cf9af4361f5e9c03f0f332923efea29619dbdd285acfa870",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 2443000000,
      "index": 2,
      "globalIndex": 14256290,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "304c149f50f2c62347bbfd7ea6a1323df5fd5542b9d94299355ad365f1c6e311",
      "mainChain": true
    },
    {
      "boxId": "0d00a3b4cfe6dd8472907b3b9cd38e92c0c7da609fb65e1908ffdc08d3a0eb79",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 178000000,
      "index": 3,
      "globalIndex": 14256291,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "bb115bbb7abb961fd492e4fc23435bf8f9e19764f40f52067e78cacf43eba5e4",
      "mainChain": true
    },
    {
      "boxId": "d316f4fee494ededbc124ad7846e95b4d7613c956d14eeda4bc496dece33ab34",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 2417000000,
      "index": 4,
      "globalIndex": 14256292,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "fec00e967b30f6892b4ada2a5d1439d2a833a3346386269a510e7b64113cdecb",
      "mainChain": true
    },
    {
      "boxId": "383fe109030cd01238777a6fa4a6e6c8340746bd621f7e61b36063679433a019",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 2763000000,
      "index": 5,
      "globalIndex": 14256293,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "52816d59b14199b1ebd5d5f0c6f0fc5b6451b457744e239e2638fb79c336e7ec",
      "mainChain": true
    },
    {
      "boxId": "84cd257cce885ff2dbfe296eb6f86f2fa53d16062743f2cb3f43fa130760a337",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 3842000000,
      "index": 6,
      "globalIndex": 14256294,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "1bb36bd1767fb2d328874452c7a1262918b8595c1390eb2100af9c0e57d31a70",
      "mainChain": true
    },
    {
      "boxId": "e6e527f5c12878b3312cef0cbcbff7476acd8a5e910ff9f8b224d2d72ac44523",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 672000000,
      "index": 7,
      "globalIndex": 14256295,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "e9aa0243c2a7864e7e9d4ee4d747c82f78bb8b7e402daf8978f2f812bc705f8f",
      "mainChain": true
    },
    {
      "boxId": "db1166a31b84fe95d8005ce3449b327bf360e9c3e0990b0ecc9a3d99b707690e",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 8232000000,
      "index": 8,
      "globalIndex": 14256296,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "9207bc0be5458a26299b27da7023a17710d3f5090e0577959f7abfbfdb29caff",
      "mainChain": true
    },
    {
      "boxId": "1e238c76d9d9c62844c4aadae9adf494f3ded801a64e1130914026f0b75ecb15",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 2242000000,
      "index": 9,
      "globalIndex": 14256297,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "9635a470ce88891bf12bf796f72dfb0e550e4840657b7a6ba69083957a89bdd0",
      "mainChain": true
    },
    {
      "boxId": "315436a8d63177ab745b93ba2a3d4c450c567b2216341aafd2659e9a6d32934b",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 167000000,
      "index": 10,
      "globalIndex": 14256298,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "761cee1b572aadf6b14020e79beb3150f886503539251ecd54a235c50d9e7d67",
      "mainChain": true
    },
    {
      "boxId": "8e79ad312306efde787475c4cdd64c61be1bbb6d45530d02753f1163a494d4ee",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 79000000,
      "index": 11,
      "globalIndex": 14256299,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "e6cab0028132db3229d8c23e92f75fd81b8a393bf7cfaa3694fb3a09a0a00338",
      "mainChain": true
    },
    {
      "boxId": "08c8aa8c6cba6bd6cef30fd856cc8431ce7043cca60dd9ed34bf674c446e23f3",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 4524000000,
      "index": 12,
      "globalIndex": 14256300,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "6b776fac5f9bd189bfbdede80caaa56db7360e700d9df98b7a1109965dd5a6a8",
      "mainChain": true
    },
    {
      "boxId": "a78da74343690061dc0312f976d32b9e6d2ab00e1ab7bb29666b7ccbca3e7083",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 1822000000,
      "index": 13,
      "globalIndex": 14256301,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "8402cfd91f6dc4a499790d21e5191929cf067d40e4daf2529729c8cb8289d48e",
      "mainChain": true
    },
    {
      "boxId": "50ac6d8d9a61e5acd6b60c49bbd64eb7f34862304b856391335c2a67a42609f3",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 2611000000,
      "index": 14,
      "globalIndex": 14256302,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "e95a6f3035b56ff29c7519fb3d32079174e923e04baff7891f01897c2be21b0c",
      "mainChain": true
    },
    {
      "boxId": "d3917e53f903ee7c829c98b4f7ea899735dc63a3cedfd70014ac486f72af8c3e",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 866000000,
      "index": 15,
      "globalIndex": 14256303,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "4a721235ead76ea9872f242b5b0a384f6001c1a05e62fc915c32233102e5a84d",
      "mainChain": true
    },
    {
      "boxId": "bbd5f595a7f0de3940fd94c0f01618049e40c6d57c59ea87daecf6078c217d14",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 1646000000,
      "index": 16,
      "globalIndex": 14256304,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "5b9d9c3120b45f5dd2d8c07d3bb31822b119567886dfb6e35a0da7e35c48f492",
      "mainChain": true
    },
    {
      "boxId": "7ad3ac86d350c94e709b56be48d6890727c8123f0fa59b3dda77475c011ea6a6",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 1208000000,
      "index": 17,
      "globalIndex": 14256305,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "18e531710930ca6ebacaf0683ad2ebb81a435d73d636f9405d3a0eb1e87e4e99",
      "mainChain": true
    },
    {
      "boxId": "090082b78d98cb7b36f194b02d8a3b036236f496444ca2921ea7418103f2ebf5",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 4400000000,
      "index": 18,
      "globalIndex": 14256306,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "e9f3c5caef68a535095c56fd9872debbc240f5beca9a9ebe5aa48897e7d9bead",
      "mainChain": true
    },
    {
      "boxId": "74e265396570abfd2ec7673798457c95278d7705fd352ddff90360a22293646e",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 878000000,
      "index": 19,
      "globalIndex": 14256307,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "1f573e4884a11ebe0f2b49e72fed772b80c8a671cb6b834f2c12f0d0c0a1765d",
      "mainChain": true
    },
    {
      "boxId": "f189d011e5f9dd6829be1e613ac7d79dc8de5ca26d1ea0ff52ac16b041222992",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 1192000000,
      "index": 20,
      "globalIndex": 14256308,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "4cb29788e8ff3bdd50731287691dd86840beae0bd28acf9b05f4d2e7063ed911",
      "mainChain": true
    },
    {
      "boxId": "761a4dec4bbea9e2060e755507930f5ae0b8c82dcbede7f38d4a1d30c3554621",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 244000000,
      "index": 21,
      "globalIndex": 14256309,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "359b70af802503ecb34acbc5b5543bcf4e19353bdf516bd3b2a0fa8218582149",
      "mainChain": true
    },
    {
      "boxId": "46e08e4f649d3aeb122259acee456fef44accfa7bf2af14fe148055fea5fde8d",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 9662000000,
      "index": 22,
      "globalIndex": 14256310,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "888a32f3245373f8fc62c9c2ae6439f8915f29f8a8a2852e87d5bc195917bc99",
      "mainChain": true
    },
    {
      "boxId": "da0cffb9f8ac38212d6f5f1b33d746f8918596b9b704aaa6c5c68cb002ae4d48",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 3317000000,
      "index": 23,
      "globalIndex": 14256311,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "545751ad61690856cd0e658396d5700fc9259605462f94ca94c29ae2929a1c76",
      "mainChain": true
    },
    {
      "boxId": "5704d816dd64a52eec2a0d2c36885b54590e24e7eb4a8a7f4fb34f65730c2155",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 1238000000,
      "index": 24,
      "globalIndex": 14256312,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "4fa95cc5464105be879bfe4cf45aabb83b1c8621fb81c6a44b77ae35071139d8",
      "mainChain": true
    },
    {
      "boxId": "b46670cb1644f49f2597feb42a877f0c5de3be75ff02021beefa13842dfa53a2",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 502000000,
      "index": 25,
      "globalIndex": 14256313,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "3e4aa83fb1b5e44635b0e7309805bfb035bd79da172cb313eee28604a4c33bf4",
      "mainChain": true
    },
    {
      "boxId": "aa9a32650ff9e6738994809fd9254f3c78f762762e5cd27defd871bd8df6f382",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 4586000000,
      "index": 26,
      "globalIndex": 14256314,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "b39c5d63b9a2ab1a90c174d6ad048151beb4c0b18a3e3fd285cf56e3897f4a66",
      "mainChain": true
    },
    {
      "boxId": "bb27c22e0043e1c634f0184b9647cb7b146b102706939272697c6dcb102307ad",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 385000000,
      "index": 27,
      "globalIndex": 14256315,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "f5a2babe517349a4cb813c0e33e51265c5860635ac708880a0a5049ffa8e9e21",
      "mainChain": true
    },
    {
      "boxId": "7047a89d85b77f455d310f4649500976223588e9a289b763fa6ea266ffdf028c",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 699000000,
      "index": 28,
      "globalIndex": 14256316,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "e5f46c4c8807fca2806ef3137233585f1893b07bbda27a8700453a68ebf765ea",
      "mainChain": true
    },
    {
      "boxId": "e81427c148bf649889aea1ae9474241204729c078548325864dbbadc6ca6ce81",
      "transactionId": "e6a4b0c65c66748cc491517450468c2e150c5ba799bfc190a98370dae4e00869",
      "blockId": "185217c541560fa3e89ba175fe66558693e841a74c5608c1fe1d87c62d4903ab",
      "value": 145000000,
      "index": 29,
      "globalIndex": 14256317,
      "creationHeight": 706001,
      "settlementHeight": 706004,
      "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": "a50a2474e5d65112020185e59d0c5d61680aad205d51b93e62483d83b9c06219",
      "mainChain": true
    }
  ],
  "size": 45644,
  "isUnconfirmed": false
}