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Transaction

5/5/2023 07:47:22 PM
ID: 1c1f90aedc...edc5
Inputs (12)
#0
96d6ed1ecb73...949b
Spent
Address:
Spectrum Finance (Yield Farm)
Output transaction:
f01e00cd45e3...acce
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#1
58299f078916...fe55
Spent
Address:
9hkfeMZj1p3r...kKvj
Output transaction:
f01e00cd45e3...acce
Settlement height:
997,403
Value:
0.39475 ERG
#2
0350dfafdcd6...6ff2
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#3
5f2b0a14d19e...0cbd
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#4
872b22a38ef4...85cb
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#5
cab76ffd5184...f9f8
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#6
5edbc993f0d9...6f9e
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#7
87dc9abe59a4...34bc
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#8
467a31c8e0e5...8c10
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#9
332ffd148843...741e
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#10
8a3bbcdc1dd5...e75a
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
#11
64d1d0fbca12...4e7b
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
a0801091804a...5761
Settlement height:
996,902
Value:
0.000522 ERG
Tokens:
Loading assets...
Outputs (23)
#0
b2f44245332a...2f85
Spent
Address:
Spectrum Finance (Yield Farm)
Spent in transaction:
e8ac3c164b01...03bc
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#1
c3b8f8d7b9d8...1a99
Spent
Address:
9hkfeMZj1p3r...kKvj
Spent in transaction:
e8ac3c164b01...03bc
Settlement height:
997,403
Value:
0.38925 ERG
#2
17c5aaaf1e19...ff8a
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#3
ad399c055156...a169
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#4
f3d33e0521ef...da62
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#5
ab3c375510d2...81d7
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#6
6993ea245d05...c091
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#7
2ee56a0bf21e...403a
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#8
72a5dde20c0b...26c7
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#9
e70bf50d1b0f...8dee
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#10
8df3a52a8d37...f24a
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#11
27bc37ca0b58...6090
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
bf13936bad11...f488
Settlement height:
997,403
Value:
0.000522 ERG
Tokens:
Loading assets...
#12
60a702c2344c...cfe1
Spent
Address:
9fvH7zjVyHGK...68C3
Spent in transaction:
f7e6bd3833d9...a083
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
0
#13
238a45234fd0...7738
Spent
Address:
9fSNgwa3YdXd...3TFJ
Spent in transaction:
41f5d3099021...2ee5
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
188.93
#14
3e17674dbf9b...7269
Spent
Address:
9gvc1cgqFcDU...GENg
Spent in transaction:
f8f0eb174ea6...29c5
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
0
#15
91d0545a1b35...6796
Spent
Address:
9hSarSwsWaSw...eCPv
Spent in transaction:
4bf7cbf09a5c...ead1
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
4
#16
fa9e8c61f681...ab8c
Spent
Address:
9fofQ7QsMmBH...MikJ
Spent in transaction:
cc2d3fa086ec...d815
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
4
#17
5df8bcd41702...3012
Unspent
Address:
9gVVxrJcPLXZ...yriZ
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
0
#18
587ec73d6d22...603a
Spent
Address:
9fSNgwa3YdXd...3TFJ
Spent in transaction:
41f5d3099021...2ee5
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
152.80
#19
f02905e3074f...e81c
Spent
Address:
9fix1oWtTWRB...oc4U
Spent in transaction:
eee871ee4c9f...f588
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
1
#20
636296c74470...9a22
Spent
Address:
9fAgL47brnLf...r6U2
Spent in transaction:
ae774519fb0b...d4ac
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
2
#21
110037904189...b4c7
Spent
Address:
9eZ7wg2HLn5J...t2e1
Spent in transaction:
45c81ebc5ca2...2cfd
Settlement height:
997,403
Value:
0.00025 ERG
Tokens:
tSPF
2
#22
9b57fd27f796...dd6e
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
cc6090f24ada...5625
Settlement height:
997,403
Value:
0.003 ERG
Transaction Details
Status: Confirmed
Size: 10.98 KB
Received time: 5/5/2023 07:47:22 PM
Included in blocks: 997,403
Confirmations: 761,227
Total coins transferred: 0.400492 ERG
Fees: 0.003 ERG
Fees per byte: 0.000000267 ERG
Raw Transaction Data
{
  "id": "1c1f90aedc44b1f2f2c3f723b2feca80d231c25279dfc2a4eef2fe881570edc5",
  "blockId": "656ebe169970ec0ee7db05ac66ccf394c4a728ef6fbff1375415d99ecb75a1e9",
  "inclusionHeight": 997403,
  "timestamp": 1683316042127,
  "index": 5,
  "globalIndex": 5149696,
  "numConfirmations": 761227,
  "inputs": [
    {
      "boxId": "96d6ed1ecb7396489117de80c5cc3f56bda05f189c85d4a8b3d88c93710d949b",
      "value": 522000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "656ebe169970ec0ee7db05ac66ccf394c4a728ef6fbff1375415d99ecb75a1e9",
      "outputTransactionId": "f01e00cd45e3ca22099377bfb9c2ebcc97ec8e568fac7d4dc0397eeb9418acce",
      "outputIndex": 0,
      "outputGlobalIndex": 28865173,
      "outputCreatedAt": 997400,
      "outputSettledAt": 997403,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 1\n3: 1\n4: 2\n5: 2\n6: 3\n7: 3\n8: 4\n9: 4\n10: 2\n11: 1\n12: 0\n13: 0\n14: 1\n15: 1\n16: 0\n17: 5\n18: 0\n19: 0\n20: 2\n21: 1\n22: 1\n23: Coll(5,8,-13,98,61,75,43,-29,-67,-71,115,123,62,101,100,79,1,17,103,-18,-5,-125,13,-103,101,32,95,2,44,-19,-92,13)\n24: 0\n25: 1\n26: 0\n27: 1\n28: 1\n29: 3\n30: 0\n31: 0\n32: 9223372036854775807\n33: 0\n34: 0\n35: 1\n36: CBigInt(1)\n37: 0\n38: 0\n39: false",
      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.tokens\n  val tuple4 = coll3(placeholder[Int](1))\n  val coll5 = SELF.R4[Coll[Int]].get\n  val l6 = SELF.R5[Long].get\n  val l7 = SELF.R6[Long].get\n  val tuple8 = coll2(placeholder[Int](2))\n  val tuple9 = coll3(placeholder[Int](3))\n  val tuple10 = coll2(placeholder[Int](4))\n  val tuple11 = coll3(placeholder[Int](5))\n  val tuple12 = coll2(placeholder[Int](6))\n  val tuple13 = coll3(placeholder[Int](7))\n  val coll14 = tuple13._1\n  val tuple15 = coll2(placeholder[Int](8))\n  val tuple16 = coll3(placeholder[Int](9))\n  val coll17 = tuple16._1\n  val l18 = tuple11._2\n  val l19 = tuple10._2 - l18\n  val l20 = tuple9._2\n  val i21 = coll5(placeholder[Int](10))\n  val i22 = HEIGHT - i21 + placeholder[Int](11)\n  val i23 = coll5(placeholder[Int](12))\n  val i24 = i22 / i23\n  val i25 = if (i22 % i23 > placeholder[Int](13)) { i24 + placeholder[Int](14) } else { i24 }\n  val i26 = coll5(placeholder[Int](15))\n  val l27 = i26.toLong\n  val l28 = l6 / l27\n  val l29 = tuple12._2 - tuple13._2\n  val l30 = tuple16._2\n  val l31 = tuple15._2 - l30\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (coll2(placeholder[Int](16)) == tuple4) && (\n              (((box1.R4[Coll[Int]].get == coll5) && (box1.R5[Long].get == l6)) && (box1.R6[Long].get == l7)) && (box1.creationInfo._1 >= SELF.creationInfo._1)\n            )\n          ) && (box1.propositionBytes == SELF.propositionBytes)\n        ) && ((((tuple8._1 == tuple9._1) && (tuple10._1 == tuple11._1)) && (tuple12._1 == coll14)) && (tuple15._1 == coll17))\n      ) && (coll2.size == placeholder[Int](17))\n    ) && if (l19 > placeholder[Long](18)) {(\n      val l32 = l19 * l27 - max(placeholder[Long](19), i25.toLong)\n      val box33 = OUTPUTS(placeholder[Int](20))\n      (\n        (\n          (l6 - l20.toBigInt + l7.toBigInt >= if (i25 <= i26) { i25 } else { i26 + placeholder[Int](21) } - placeholder[Int](22).toLong * l28.toBigInt) && (\n            l19 == !l29\n          )\n        ) && (l32 == !l31)\n      ) && (\n        (\n          (\n            ((blake2b256(box33.propositionBytes) == placeholder[Coll[Byte]](23)) && ((coll14, l19) == box33.tokens(placeholder[Int](24)))) && (\n              (coll17, l32) == box33.tokens(placeholder[Int](25))\n            )\n          ) && box33.R6[SigmaProp].isDefined\n        ) && (box33.R7[Coll[Byte]].get == tuple4._1)\n      )\n    )} else {\n      if (l19 < placeholder[Long](26)) {\n        (\n          (\n            (l6 - l20.toBigInt + l7.toBigInt >= if (i25 <= i26) { i25 } else { i26 + placeholder[Int](27) } - placeholder[Int](28).toLong * l28.toBigInt) || (\n              HEIGHT >= i21 + i26 * i23 + coll5(placeholder[Int](29))\n            )\n          ) && (l29 == !l19)\n        ) && (l31 >= if (i25 > i26) { placeholder[Long](30) } else { l29 * l27 - max(placeholder[Long](31), i25.toLong) })\n      } else {(\n        val i32 = box1.R7[Int].get\n        val i33 = i26 - i32\n        val l34 = i33.toLong\n        val l35 = placeholder[Long](32) - l30 - l18 * l34\n        if ((l35 > placeholder[Long](33)) && (l31 > placeholder[Long](34))) {\n          (\n            (\n              ((i32 <= i25 - placeholder[Int](35)) && (l20 - l34 * l28 <= l28 + l7)) && (\n                !tuple8._2 - l20.toBigInt <= l20.toBigInt - l6.toBigInt * i33.toBigInt / i26.toBigInt - placeholder[BigInt](36) * l31.toBigInt / l35.toBigInt\n              )\n            ) && (l19 == placeholder[Long](37))\n          ) && (l29 == placeholder[Long](38))\n        } else { placeholder[Boolean](39) }\n      )}\n    }\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "8d49ef70ab015d79cb9ab523adf3ccb0b7d05534c598e4ddf8acb8b2b420b463",
          "index": 0,
          "amount": 1,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "50eab1afc495420c17c0df5154584cf09d9167263fffc99c25e3e0ae4b26fe00",
          "index": 1,
          "amount": 204788486167,
          "name": "tSPF",
          "decimals": 6,
          "type": "EIP-004"
        },
        {
          "tokenId": "cb0b42a58d38104c906444b43d1e03c8d553f79b06244cb4c98d93b46875040e",
          "index": 2,
          "amount": 13910387269734,
          "name": "706fb118_50eab1af_LP",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "a875b8dd63b401d988ab8af0f46b89afe5c6c264edde02f6b8819f094e24cf5e",
          "index": 3,
          "amount": 9223358126467506000,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "a6822e28f865c39f96004ded6f63c4fda4bcef48714d374775b886bc9f0dc313",
          "index": 4,
          "amount": 9222185083875299000,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1004e807fa01f0a777d00f",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[500,125,977400,1000]"
        },
        "R5": {
          "serializedValue": "0580e0a596bb11",
          "sigmaType": "SLong",
          "renderedValue": "300000000000"
        },
        "R6": {
          "serializedValue": "05d804",
          "sigmaType": "SLong",
          "renderedValue": "300"
        },
        "R7": {
          "serializedValue": "0450",
          "sigmaType": "SInt",
          "renderedValue": "40"
        }
      }
    },
    {
      "boxId": "58299f078916eca3eacf1619adab86f9af8fb34e54cb925230699f8f0e2afe55",
      "value": 394750000,
      "index": 1,
      "spendingProof": "abe1c5b3e4a9e4f73ff1e875cce35ebbb1c3c2a72e71fb4efb8bb81e06f52914bfba630c2422d342a50aef3421fa98f207065e20f99936be",
      "outputBlockId": "656ebe169970ec0ee7db05ac66ccf394c4a728ef6fbff1375415d99ecb75a1e9",
      "outputTransactionId": "f01e00cd45e3ca22099377bfb9c2ebcc97ec8e568fac7d4dc0397eeb9418acce",
      "outputIndex": 1,
      "outputGlobalIndex": 28865174,
      "outputCreatedAt": 997400,
      "outputSettledAt": 997403,
      "ergoTree": "0008cd03a9fb4e3874c496d5495ce3690862a03ab4d249f097155f9945b01b4fb1bb454b",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(a9fb4e,56da23,...)))}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "assets": [
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "537065637472756d205946207374616b696e672062756e646c65"
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        "R5": {
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          "sigmaType": "SSigmaProp",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "assets": [
        {
          "tokenId": "a875b8dd63b401d988ab8af0f46b89afe5c6c264edde02f6b8819f094e24cf5e",
          "index": 0,
          "amount": 10654937968,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
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          "index": 1,
          "amount": 916324665248,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "aa0916461dafa1f5188e38a69cf6cc1180952a651eaad9f65cc53c6dfef8e118",
          "index": 2,
          "amount": 1,
          "name": "Spectrum YF staking bundle",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e1a537065637472756d205946207374616b696e672062756e646c65",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "537065637472756d205946207374616b696e672062756e646c65"
        },
        "R5": {
          "serializedValue": "0ea80154686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203864343965663730616230313564373963623961623532336164663363636230623764303535333463353938653464646638616362386232623432306234363329206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "54686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203864343965663730616230313564373963623961623532336164663363636230623764303535333463353938653464646638616362386232623432306234363329206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e"
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        "R6": {
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          "sigmaType": "SSigmaProp",
          "renderedValue": "02556a448a4f4ed82775e7a0374dd74bd40312a4c26617bfb3fc1d5f308d304e64"
        },
        "R7": {
          "serializedValue": "0e208d49ef70ab015d79cb9ab523adf3ccb0b7d05534c598e4ddf8acb8b2b420b463",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "8d49ef70ab015d79cb9ab523adf3ccb0b7d05534c598e4ddf8acb8b2b420b463"
        }
      }
    },
    {
      "boxId": "64d1d0fbca126e0f3171c29426cefa5eb17fd4f39342f88397f76834ce184e7b",
      "value": 522000,
      "index": 11,
      "spendingProof": null,
      "outputBlockId": "417a725bda10bd616539030d1e1b49ba7d90963129953b40d98c1ad8c5a84781",
      "outputTransactionId": "a0801091804a20a2ba40d66f216674795c0af228c4ac64372b22e38f58145761",
      "outputIndex": 11,
      "outputGlobalIndex": 28843291,
      "outputCreatedAt": 996900,
      "outputSettledAt": 996902,
      "ergoTree": "19bc04210400040004040404040004020601010601000400050004020404040205feffffffffffffffff010408040004020502040405020402040004000101010005000404040004060404040205fcffffffffffffffff010100d80dd601b2a5730000d602db63087201d603e4c6a7070ed604b2a4730100d605db63087204d6068cb2720573020002d607998cb27202730300027206d608e4c6a70608d609db6308a7d60ab27209730400d60bb27205730500d60c7306d60d7307d1ed938cb27202730800017203959372077309d80cd60eb2a5e4e3000400d60fb2a5e4e3010400d610b2e4c672040410730a00d611c672010804d61299721095e67211e47211e4c672010704d6138cb27209730b0001d614db6308720fd615b27209730c00d6168c721502d6177e721205d6189972169c72178c720a02d6199d9c99997e8c720b02069d9c7ee4c672040505067e7212067e721006720c7e7218067e9999730d8cb27205730e00029c7206721706eded93c2720ed07208edededed93e4c6720f0608720893e4c6720f070e720393c2720fc2a795917212730fd801d61ab27214731000eded93860272137311b27214731200938c721a018c721501939972168c721a02721893860272137313b2721473140093b27214731500720a95917219720dd801d61ab2db6308720e731600ed938c721a018c720b01927e8c721a0206997219720c95937219720d73177318958f7207731993b2db6308b2a4731a00731b0086029593b17209731c8cb27209731d00018cb27209731e0001731f7320",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 2\n4: 0\n5: 1\n6: CBigInt(1)\n7: CBigInt(0)\n8: 0\n9: 0\n10: 1\n11: 2\n12: 1\n13: 9223372036854775807\n14: 4\n15: 0\n16: 1\n17: 1\n18: 2\n19: 1\n20: 1\n21: 0\n22: 0\n23: true\n24: false\n25: 0\n26: 2\n27: 0\n28: 3\n29: 2\n30: 1\n31: 9223372036854775806\n32: false",
      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "assets": [
        {
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          "decimals": 0,
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        },
        {
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        {
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          "amount": 1,
          "name": "Spectrum YF staking bundle",
          "decimals": 0,
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      ],
      "additionalRegisters": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "537065637472756d205946207374616b696e672062756e646c65"
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        "R5": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "54686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203864343965663730616230313564373963623961623532336164663363636230623764303535333463353938653464646638616362386232623432306234363329206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e"
        },
        "R6": {
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          "sigmaType": "SSigmaProp",
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    }
  ],
  "dataInputs": [],
  "outputs": [
    {
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      "transactionId": "1c1f90aedc44b1f2f2c3f723b2feca80d231c25279dfc2a4eef2fe881570edc5",
      "blockId": "656ebe169970ec0ee7db05ac66ccf394c4a728ef6fbff1375415d99ecb75a1e9",
      "value": 522000,
      "index": 0,
      "globalIndex": 28865196,
      "creationHeight": 997400,
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.tokens\n  val tuple4 = coll3(placeholder[Int](1))\n  val coll5 = SELF.R4[Coll[Int]].get\n  val l6 = SELF.R5[Long].get\n  val l7 = SELF.R6[Long].get\n  val tuple8 = coll2(placeholder[Int](2))\n  val tuple9 = coll3(placeholder[Int](3))\n  val tuple10 = coll2(placeholder[Int](4))\n  val tuple11 = coll3(placeholder[Int](5))\n  val tuple12 = coll2(placeholder[Int](6))\n  val tuple13 = coll3(placeholder[Int](7))\n  val coll14 = tuple13._1\n  val tuple15 = coll2(placeholder[Int](8))\n  val tuple16 = coll3(placeholder[Int](9))\n  val coll17 = tuple16._1\n  val l18 = tuple11._2\n  val l19 = tuple10._2 - l18\n  val l20 = tuple9._2\n  val i21 = coll5(placeholder[Int](10))\n  val i22 = HEIGHT - i21 + placeholder[Int](11)\n  val i23 = coll5(placeholder[Int](12))\n  val i24 = i22 / i23\n  val i25 = if (i22 % i23 > placeholder[Int](13)) { i24 + placeholder[Int](14) } else { i24 }\n  val i26 = coll5(placeholder[Int](15))\n  val l27 = i26.toLong\n  val l28 = l6 / l27\n  val l29 = tuple12._2 - tuple13._2\n  val l30 = tuple16._2\n  val l31 = tuple15._2 - l30\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (coll2(placeholder[Int](16)) == tuple4) && (\n              (((box1.R4[Coll[Int]].get == coll5) && (box1.R5[Long].get == l6)) && (box1.R6[Long].get == l7)) && (box1.creationInfo._1 >= SELF.creationInfo._1)\n            )\n          ) && (box1.propositionBytes == SELF.propositionBytes)\n        ) && ((((tuple8._1 == tuple9._1) && (tuple10._1 == tuple11._1)) && (tuple12._1 == coll14)) && (tuple15._1 == coll17))\n      ) && (coll2.size == placeholder[Int](17))\n    ) && if (l19 > placeholder[Long](18)) {(\n      val l32 = l19 * l27 - max(placeholder[Long](19), i25.toLong)\n      val box33 = OUTPUTS(placeholder[Int](20))\n      (\n        (\n          (l6 - l20.toBigInt + l7.toBigInt >= if (i25 <= i26) { i25 } else { i26 + placeholder[Int](21) } - placeholder[Int](22).toLong * l28.toBigInt) && (\n            l19 == !l29\n          )\n        ) && (l32 == !l31)\n      ) && (\n        (\n          (\n            ((blake2b256(box33.propositionBytes) == placeholder[Coll[Byte]](23)) && ((coll14, l19) == box33.tokens(placeholder[Int](24)))) && (\n              (coll17, l32) == box33.tokens(placeholder[Int](25))\n            )\n          ) && box33.R6[SigmaProp].isDefined\n        ) && (box33.R7[Coll[Byte]].get == tuple4._1)\n      )\n    )} else {\n      if (l19 < placeholder[Long](26)) {\n        (\n          (\n            (l6 - l20.toBigInt + l7.toBigInt >= if (i25 <= i26) { i25 } else { i26 + placeholder[Int](27) } - placeholder[Int](28).toLong * l28.toBigInt) || (\n              HEIGHT >= i21 + i26 * i23 + coll5(placeholder[Int](29))\n            )\n          ) && (l29 == !l19)\n        ) && (l31 >= if (i25 > i26) { placeholder[Long](30) } else { l29 * l27 - max(placeholder[Long](31), i25.toLong) })\n      } else {(\n        val i32 = box1.R7[Int].get\n        val i33 = i26 - i32\n        val l34 = i33.toLong\n        val l35 = placeholder[Long](32) - l30 - l18 * l34\n        if ((l35 > placeholder[Long](33)) && (l31 > placeholder[Long](34))) {\n          (\n            (\n              ((i32 <= i25 - placeholder[Int](35)) && (l20 - l34 * l28 <= l28 + l7)) && (\n                !tuple8._2 - l20.toBigInt <= l20.toBigInt - l6.toBigInt * i33.toBigInt / i26.toBigInt - placeholder[BigInt](36) * l31.toBigInt / l35.toBigInt\n              )\n            ) && (l19 == placeholder[Long](37))\n          ) && (l29 == placeholder[Long](38))\n        } else { placeholder[Boolean](39) }\n      )}\n    }\n  )\n}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "transactionId": "1c1f90aedc44b1f2f2c3f723b2feca80d231c25279dfc2a4eef2fe881570edc5",
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      "globalIndex": 28865217,
      "creationHeight": 997400,
      "settlementHeight": 997403,
      "ergoTree": "0008cd0204aceb23d37f2caac9eb8eff06b2d6d3dd175055230687313e61c20153803f29",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(4aceb2,88af02,...)))}",
      "address": "9eZ7wg2HLn5JA8QEyMQbkuDaSooqt9vKh5soHxc1tgrRDaWt2e1",
      "assets": [
        {
          "tokenId": "50eab1afc495420c17c0df5154584cf09d9167263fffc99c25e3e0ae4b26fe00",
          "index": 0,
          "amount": 1836353,
          "name": "tSPF",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "45c81ebc5ca20081b3f81fe861de6f454fbe276c95cdcf55e5508fa762b32cfd",
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    },
    {
      "boxId": "9b57fd27f796fb87fbff895a0f41fa021b30a1dfb01502f8cae9a2cf942edd6e",
      "transactionId": "1c1f90aedc44b1f2f2c3f723b2feca80d231c25279dfc2a4eef2fe881570edc5",
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      "ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
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      "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)}",
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      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "cc6090f24ada963d9dab3367e95ca985d8fa99831672fa38df1d6c5075255625",
      "mainChain": true
    }
  ],
  "size": 11247,
  "isUnconfirmed": false
}