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Transaction

8/29/2023 04:50:16 PM
ID: d3fba92962...cf78
Inputs (12)
#0
d2ffe39dcce6...d704
Spent
Address:
Spectrum Finance (Yield Farm)
Output transaction:
98f8475e1cea...9a05
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#1
fbf652d5b2fd...2c20
Spent
Address:
9h9y3T3W84Ut...Cwxc
Output transaction:
98f8475e1cea...9a05
Settlement height:
1,079,654
Value:
0.232706 ERG
#2
bfc65dca43d7...f647
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
621082c75b04...73bc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#3
7dc308c8b90e...081d
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
621082c75b04...73bc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#4
e7e05d639279...c78b
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
621082c75b04...73bc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#5
b985aa5bb09a...d9f1
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
21409cd6d0dd...49dc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#6
e182bfa8dc19...264b
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
21409cd6d0dd...49dc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#7
e52422a09d83...82f9
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
21409cd6d0dd...49dc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#8
07312103d188...b608
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
21409cd6d0dd...49dc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#9
54c87e76b0be...7543
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
21409cd6d0dd...49dc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#10
8a7f17589029...963d
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
21409cd6d0dd...49dc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
#11
d4a3ae325015...3c17
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
21409cd6d0dd...49dc
Settlement height:
1,078,933
Value:
0.000522 ERG
Tokens:
Loading assets...
Outputs (23)
#0
47950479fab0...a6db
Spent
Address:
Spectrum Finance (Yield Farm)
Spent in transaction:
a8874adaa2db...36db
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#1
9bb3be8ac483...f318
Spent
Address:
9h9y3T3W84Ut...Cwxc
Spent in transaction:
a8874adaa2db...36db
Settlement height:
1,079,654
Value:
0.227206 ERG
#2
f41be6fab047...3c19
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
c41229cabd3c...beab
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#3
4a6bf8508178...8df7
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
c41229cabd3c...beab
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#4
3d7a0970aba4...de17
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
c41229cabd3c...beab
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#5
ed0d0e1415bc...fc13
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
c41229cabd3c...beab
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#6
930e1cf9a0ae...16cc
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
d807e2e430af...34c1
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#7
abec2f35c6f8...28b3
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
d807e2e430af...34c1
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#8
4a3848de6f6c...8e2b
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
d807e2e430af...34c1
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#9
63f04bf1521d...68d5
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
d807e2e430af...34c1
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#10
b639c7012572...5de7
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
d807e2e430af...34c1
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#11
c439ec0595ca...e9c6
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
d807e2e430af...34c1
Settlement height:
1,079,654
Value:
0.000522 ERG
Tokens:
Loading assets...
#12
f26716f5baed...d6b8
Spent
Address:
9hGopx2RHDdn...N8WF
Spent in transaction:
af8f2902b7d5...d50a
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
6
#13
651910a4bce2...79bb
Spent
Address:
9f3TrUwmZxd7...2omY
Spent in transaction:
5669524cf6d9...b82d
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
0
#14
5676f211fca9...6877
Spent
Address:
9gzAmxRpSkez...5TCH
Spent in transaction:
7e5e259f6315...c29e
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
19.52
#15
941185b3daf2...5f3d
Spent
Address:
9fZ96JpYU1LV...VEQ1
Spent in transaction:
a6c6a7d8eb5b...1e5f
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
6
#16
dab49dc70c6c...2586
Spent
Address:
Baseless Bureau of Investigation (Giga Whale)
Spent in transaction:
50789e98c3a8...8202
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
10.69
#17
e982bd448a9f...8909
Spent
Address:
9iGnfSDLEVNP...9uMK
Spent in transaction:
a56326bc80b5...d7ac
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
0
#18
6f7f1f7051eb...19ec
Spent
Address:
9fmksSKWcRfH...cKoH
Spent in transaction:
1fc225f36d43...39c1
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
4
#19
a3d33c42a0a5...dc36
Spent
Address:
9eZTChHgGfJu...hAER
Spent in transaction:
6f760186a508...6562
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
0
#20
b743be5d2f80...f861
Spent
Address:
Baseless Bureau of Investigation (Giga Whale)
Spent in transaction:
50789e98c3a8...8202
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
10.81
#21
4ec739989f32...cf75
Unspent
Address:
9iMcjdPpfe63...Qtj6
Settlement height:
1,079,654
Value:
0.00025 ERG
Tokens:
SPF
2
#22
574e55612a65...58b4
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
17d71711e4b9...7235
Settlement height:
1,079,654
Value:
0.003 ERG
Transaction Details
Status: Confirmed
Size: 10.96 KB
Received time: 8/29/2023 04:50:16 PM
Included in blocks: 1,079,654
Confirmations: 686,250
Total coins transferred: 0.238448 ERG
Fees: 0.003 ERG
Fees per byte: 0.000000267 ERG
Raw Transaction Data
{
  "id": "d3fba929623fed1e744b63abfa7b6b1312ec0c150a58d1731aca0da506e5cf78",
  "blockId": "3d8d7aa34a4497dcf7a333b6702cf469573bcc1e5e3c4166f8e55f3056fc772e",
  "inclusionHeight": 1079654,
  "timestamp": 1693327816087,
  "index": 23,
  "globalIndex": 5744557,
  "numConfirmations": 686250,
  "inputs": [
    {
      "boxId": "d2ffe39dcce691f08d86564dd69c76e6319db8e3422af8cd70397e31503ed704",
      "value": 522000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "3d8d7aa34a4497dcf7a333b6702cf469573bcc1e5e3c4166f8e55f3056fc772e",
      "outputTransactionId": "98f8475e1cea7d590a6dd27c4423f1909aea7fbd1639f2b57faa901859f59a05",
      "outputIndex": 0,
      "outputGlobalIndex": 32176276,
      "outputCreatedAt": 1079650,
      "outputSettledAt": 1079654,
      "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": "2JowFgqdee4yFVaXNsYuiAh1ge7HGxNSaDLiXQRKhtCYYRKgwMCeqMPi54qxpovt5TtjRVNNRabtZ7awzrcnqnmALG2Hjkwe2okjFn9odM7M3uhA9RQ2uBkkVsrY1P3FW8bUTx6qRjy4yHdtdS8YUzFCvmGZVHLteknL6RN9dueHbpLYRkyV2e5mYEzptufdxy81DwNpJphyJa9Y21ELHo75vk2t24kZS5Lgt5GDByQHRu3G4GTnPb4vMvew4wUFJh8xAwM1ffoEG946YZaWkSu48UUV4tw6Y5a4uDxZPEEiSDM36wookGfTixFeWVfM9YApPytQm8y1L1bsbcocQ9JTvBjixevx1BRagnvaJrwduuDbKYr3wwpo9PfK85xXprxrFgHBVwEof9gQs5TQFJ3ddKf1pftx6SJrHyNygX6CS4Vm3TG9dU32bs8inxSn4eVdwfRdhNiECZavPBBrzgfa9ismVpkwrcNbFZrAdNSFUpoKfiuFcsP6Be5tsE4ZsPD9sWEArhbGPqya88U8TftP9DqoD3xVPUmhMsB6pb6GfwQ1QxsenMhynSMBZ4fc6eyjdZWvzWeBKKs6AbVMX6EsSoptPvsbvpd664kBq99DsZ5Br6rQGjPDM1zPYsCpGUSW849qigHzHyNmYUCoVkDgfQA26TYKwFPLi7rxsJbSfAEhwQj5czRmfg11HafTYMcuSgryKP8ZzxTfTj5LxZFsXVjY9JWScT1tA5ZFjXZHxGENBporNPMbqWzusqMKvmyzTkZDwwyJV6nzcAFRDEjHd4MjzzsHbztt9XoYtWcYyKCYyMiAxsEqvc7VvuKXvTMEyzHnR1dSpqoP6bKpCwNKKZvrYX35GdxNdEKzQS6ccbNe98zvFQPrgQPa7BjYs1hgCWv6LLLWmqhhy9J6ca332st262t1BYjVLhYLEHSvLbsmM36hDtDjyoniTuW3zVmN51nV7bkZU1L1PQobFqp7uLvdieFt234Pz2RBgezeVTqkKqJLv7D2xKveVTUGJqsM8P7BghcLTyzEY9CZ3dXZRQVh2sXbhQEFqHdKpXL92eZTLZbg1AQYRpfL2p8AVVrbeWEuha3gmA5mv95zkmi5MPbDtxEekDaTLc9KXoWtSEPSy8zRMyhiws5",
      "assets": [
        {
          "tokenId": "5f22cb20453e0856acb4b40e4ee2430e4b73a5abe4e72a0b2235a0adfb48a2be",
          "index": 0,
          "amount": 1,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "9a06d9e545a41fd51eeffc5e20d818073bf820c635e2a9d922269913e0de369d",
          "index": 1,
          "amount": 1297267178329,
          "name": "SPF",
          "decimals": 6,
          "type": "EIP-004"
        },
        {
          "tokenId": "c7e22029868ecba3d43c385bb42b8a1c96d0114ad5261ec7e0d27a6f24254f92",
          "index": 2,
          "amount": 32517372884860,
          "name": "Ergo_Spectrum Finance_LP",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "8c877434025cc85896ef2038d7ee40e0868bd3f2776c9f4a4e3d85bcaf512b10",
          "index": 3,
          "amount": 9223339519481891000,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "b970177c79ee09a9d31602c3fa97afa04ed7e64a1e3e09e6d4469039abd8303d",
          "index": 4,
          "amount": 9218311364903169000,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1004a00be802a4cc8101a00b",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[720,180,1061650,720]"
        },
        "R5": {
          "serializedValue": "0580e0bcefa757",
          "sigmaType": "SLong",
          "renderedValue": "1500000000000"
        },
        "R6": {
          "serializedValue": "059003",
          "sigmaType": "SLong",
          "renderedValue": "200"
        },
        "R7": {
          "serializedValue": "0432",
          "sigmaType": "SInt",
          "renderedValue": "25"
        }
      }
    },
    {
      "boxId": "fbf652d5b2fdd0faa1e901150eda3f87e25932707c4be8243fe9ee6cf7d02c20",
      "value": 232706000,
      "index": 1,
      "spendingProof": "32ff6bf5298c7ad47b2dafd1ba677caa91dc668a75d5dd073a8d148a1817ce2738504db4eee1039fea8ae4896ff910041078302c21eea521",
      "outputBlockId": "3d8d7aa34a4497dcf7a333b6702cf469573bcc1e5e3c4166f8e55f3056fc772e",
      "outputTransactionId": "98f8475e1cea7d590a6dd27c4423f1909aea7fbd1639f2b57faa901859f59a05",
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      "outputGlobalIndex": 32176277,
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      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(5b30e5,570728,...)))}",
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      "assets": [
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "537065637472756d205946207374616b696e672062756e646c65"
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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": [
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          "sigmaType": "Coll[SByte]",
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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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      "assets": [
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "537065637472756d205946207374616b696e672062756e646c65"
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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": [
        {
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          "index": 0,
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          "name": "",
          "decimals": 0,
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        {
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          "index": 1,
          "amount": 6164713794876,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
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          "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": "0ea80154686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203566323263623230343533653038353661636234623430653465653234333065346237336135616265346537326130623232333561306164666234386132626529206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "54686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203566323263623230343533653038353661636234623430653465653234333065346237336135616265346537326130623232333561306164666234386132626529206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e"
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        "R6": {
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          "sigmaType": "SSigmaProp",
          "renderedValue": "023009dee1bf10a97e8e3615f74160c37577e8e9519a15d7fe36a8ce014c02bc1c"
        },
        "R7": {
          "serializedValue": "0e205f22cb20453e0856acb4b40e4ee2430e4b73a5abe4e72a0b2235a0adfb48a2be",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "5f22cb20453e0856acb4b40e4ee2430e4b73a5abe4e72a0b2235a0adfb48a2be"
        }
      }
    },
    {
      "boxId": "d4a3ae3250152bf70e85e44f00d87560ad3797539d15ded56fc08bc5d6833c17",
      "value": 522000,
      "index": 11,
      "spendingProof": null,
      "outputBlockId": "c82991f2c9024d1e05d4d0bdf33e353f43e081e91444298adb2f559548bc0cec",
      "outputTransactionId": "21409cd6d0dd0d483d50837bea144679e481594bc731206ff47edc7354c849dc",
      "outputIndex": 8,
      "outputGlobalIndex": 32150287,
      "outputCreatedAt": 1078930,
      "outputSettledAt": 1078933,
      "ergoTree": "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",
      "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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        {
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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"
        },
        "R5": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "54686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203566323263623230343533653038353661636234623430653465653234333065346237336135616265346537326130623232333561306164666234386132626529206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e"
        },
        "R6": {
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          "sigmaType": "SSigmaProp",
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      }
    }
  ],
  "dataInputs": [],
  "outputs": [
    {
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      "transactionId": "d3fba929623fed1e744b63abfa7b6b1312ec0c150a58d1731aca0da506e5cf78",
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      "value": 522000,
      "index": 0,
      "globalIndex": 32176299,
      "creationHeight": 1079650,
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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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      "boxId": "4ec739989f32811753e174da5e2408a86397b1e0bc9bc7fa3fcfd272ba1bcf75",
      "transactionId": "d3fba929623fed1e744b63abfa7b6b1312ec0c150a58d1731aca0da506e5cf78",
      "blockId": "3d8d7aa34a4497dcf7a333b6702cf469573bcc1e5e3c4166f8e55f3056fc772e",
      "value": 250000,
      "index": 21,
      "globalIndex": 32176320,
      "creationHeight": 1079650,
      "settlementHeight": 1079654,
      "ergoTree": "0008cd03f956ed36590fef6267a974168242d8cfcfe988ddca0c10f0191f7b96d52396fc",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(f956ed,7d53d8,...)))}",
      "address": "9iMcjdPpfe63xjcyDUh1s1a2j8ZjUG3VEGK9mMwfutJB7dvQtj6",
      "assets": [
        {
          "tokenId": "9a06d9e545a41fd51eeffc5e20d818073bf820c635e2a9d922269913e0de369d",
          "index": 0,
          "amount": 1735988,
          "name": "SPF",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "574e55612a65ba3bc9d76933da9823db1ce339216b4021919b91bba7db4e58b4",
      "transactionId": "d3fba929623fed1e744b63abfa7b6b1312ec0c150a58d1731aca0da506e5cf78",
      "blockId": "3d8d7aa34a4497dcf7a333b6702cf469573bcc1e5e3c4166f8e55f3056fc772e",
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      "index": 22,
      "globalIndex": 32176321,
      "creationHeight": 1079650,
      "settlementHeight": 1079654,
      "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)}",
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      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "17d71711e4b92d28f40283aad86bc8e96e8020414122bc63f87ab01e52b97235",
      "mainChain": true
    }
  ],
  "size": 11220,
  "isUnconfirmed": false
}