Transaction
ID: dc5073f59f...6f95
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.67810716 ERG
Tokens:
Loading assets...
Outputs (3)
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.67700716 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 139,836
Total coins transferred: 0.67910716 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000333 ERG
Raw Transaction Data
{
"id": "dc5073f59f78a263835902b6d29654d57dbff3f16426293d59e8d20614bc6f95",
"blockId": "28e8b32907879c69a73747ed3d050c04a8c0a56b592b914d28ecd4463d73dec6",
"inclusionHeight": 1628279,
"timestamp": 1759767287419,
"index": 7,
"globalIndex": 9578745,
"numConfirmations": 139836,
"inputs": [
{
"boxId": "6bfd659273f07262f19e83bf7dac73ce95d3a790c9c1f747c227895610d311bf",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "19ea0d436f130e0be77fd07a9e864b71c91d9289bd31a8f155ec4ce4ed682e1d",
"outputTransactionId": "8f76ca9b4075314a596a00b8fb6432979e9e84940826c329539b208d17cf197c",
"outputIndex": 0,
"outputGlobalIndex": 50677826,
"outputCreatedAt": 1628271,
"outputSettledAt": 1628273,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(101,119,28,62,-51,70,113,61,-81,18,-95,-1,100,-5,26,-65,119,24,-43,-117,102,-33,97,104,101,-23,-116,-42,40,-25,-121,-44)\n2: 0\n3: 2\n4: 1\n5: 0\n6: 1\n7: 0\n8: true\n9: Coll(73,50,-82,23,-85,126,-72,-71,82,-53,15,-90,33,-31,12,-20,20,-78,-91,27,66,-39,-55,-70,-65,50,-113,-115,-84,107,59,79)\n10: 1\n11: false\n12: 0\n13: false\n14: true\n15: 1\n16: 0\n17: 1\n18: 1\n19: 0\n20: 1\n21: 2\n22: 3\n23: 30\n24: false\n25: false\n26: false\n27: 2\n28: 0\n29: 5\n30: 1000000\n31: 1000000\n32: Coll(114,105,45,-9,48,-89,-65,56,-77,-42,-39,73,-83,-46,50,-109,111,-59,-50,-71,47,125,-110,-15,44,1,-77,0,90,-56,-120,-47)\n33: 1\n34: 2\n35: 30\n36: 1\n37: 1000000\n38: false",
"ergoTreeScript": "{\n val l1 = HEIGHT.toLong\n val coll2 = SELF.R8[Coll[Long]].get\n val l3 = coll2(placeholder[Int](0))\n val coll4 = placeholder[Coll[Byte]](1)\n val coll5 = SELF.R6[Coll[Byte]].get\n val coll6 = SELF.tokens(placeholder[Int](2))._1\n val l7 = coll2(placeholder[Int](3))\n val l8 = coll2(placeholder[Int](4))\n val tuple9 = SELF.R5[(Coll[Byte], Long)].get\n val coll10 = SELF.R9[Coll[Byte]].get\n sigmaProp((SELF.R4[Int].get == placeholder[Int](5)) && (if (l1 >= l3) {(\n val coll11 = OUTPUTS.filter({(box11: Box) => blake2b256(box11.propositionBytes) == coll4 })\n if (coll11.size == placeholder[Int](6)) {(\n val box12 = coll11(placeholder[Int](7))\n val tuple13 = box12.R5[(Coll[Byte], Coll[Byte])].get\n val coll14 = tuple13._1\n val coll15 = tuple13._2\n if (((blake2b256(coll14) == coll5) && (blake2b256(box12.propositionBytes) == coll4)) && if (coll15 == Coll[Byte]()) { placeholder[Boolean](8) } else {(\n val coll16 = CONTEXT.dataInputs.filter({(box16: Box) => ((blake2b256(box16.propositionBytes) == placeholder[Coll[Byte]](9)) && (box16.R6[Coll[Byte]].get == coll6)) && (box16.R5[Coll[Byte]].get == coll15) })\n if (coll16.size != placeholder[Int](10)) { placeholder[Boolean](11) } else {(\n val box17 = coll16(placeholder[Int](12))\n (box17.R9[Coll[Long]].get.fold(placeholder[Boolean](13), {(tuple18: (Boolean, Long)) =>\n val bool20 = tuple18._1\n if (bool20) { bool20 } else { if (blake2b256(box17.R7[Coll[Byte]].get.append(longToByteArray(tuple18._2)).append(box17.R8[Coll[Byte]].get).append(coll14)) == box17.R5[Coll[Byte]].get) { placeholder[Boolean](14) } else { bool20 } }\n }) && (box17.value >= l7)) && (box17.creationInfo._1.toLong < l3)\n )}\n )}) {(\n val coll16 = SELF.R7[Coll[Coll[Byte]]].get\n val coll17 = CONTEXT.dataInputs.filter({(box17: Box) => ((box17.tokens.size == placeholder[Int](15)) && (box17.R5[Coll[Byte]].get == coll6)) && box17.R6[(Boolean, Long)].get._1 })\n val coll18 = coll17.map({(box18: Box) => box18.tokens(placeholder[Int](16))._1 })\n ((coll16.size == coll17.size) && coll16.forall({(coll19: Coll[Byte]) => coll18.exists({(coll21: Coll[Byte]) => coll21 == coll19 }) })) && ((((((((((box12.value >= l8) && (box12.tokens.filter({(tuple19: (Coll[Byte], Long)) => tuple19._1 == coll6 }).size == placeholder[Int](17))) && (box12.R4[Int].get == placeholder[Int](18))) && (box12.R6[Coll[Coll[Byte]]].get == coll18)) && (box12.R7[Coll[Long]].get(placeholder[Int](19)) == l3)) && (box12.R7[Coll[Long]].get(placeholder[Int](20)) == l8)) && (box12.R7[Coll[Long]].get(placeholder[Int](21)) == l7)) && (box12.R7[Coll[Long]].get(placeholder[Int](22)) >= l1 + placeholder[Long](23))) && (box12.R8[(Coll[Byte], Long)].get._2 == tuple9._2)) && (box12.R9[(Coll[Byte], Coll[Byte])].get == (tuple9._1, coll10)))\n )} else { placeholder[Boolean](24) }\n )} else { placeholder[Boolean](25) }\n )} else { placeholder[Boolean](26) } || if ((l1 < l3) && (OUTPUTS.size >= placeholder[Int](27))) {(\n val box11 = OUTPUTS(placeholder[Int](28))\n val l12 = l8 / placeholder[Long](29)\n val l13 = l8 - l12\n val bool14 = l13 < placeholder[Long](30)\n val l15 = if (bool14) { placeholder[Long](31) } else { l13 }\n (((((((((blake2b256(box11.propositionBytes) == placeholder[Coll[Byte]](32)) && (box11.value >= l15)) && (box11.tokens.filter({(tuple16: (Coll[Byte], Long)) => tuple16._1 == coll6 }).size == placeholder[Int](33))) && (box11.R4[Int].get == placeholder[Int](34))) && (box11.R5[Long].get >= l1 + placeholder[Long](35))) && (blake2b256(box11.R6[Coll[Byte]].get) == coll5)) && (box11.R7[Long].get == l15)) && (box11.R8[Long].get == l3)) && (box11.R9[Coll[Byte]].get == coll10)) && (OUTPUTS(placeholder[Int](36)).value >= if (bool14) { l8 - placeholder[Long](37) } else { l12 })\n )} else { placeholder[Boolean](38) }))\n}",
"address": "BrTS7hmXviNh8rusGUpP3166BJAZS1tGMYXgH2Y9V31df1k5P4EXbCLeUDjbcvAC9V5KmhAUtn3W3e8nvrpwKrYFHUaWV7yYS6v3Jii1s4rzcsbGgPqJvrtBhnuSaVJgax7AbCySwADz9v2rubHSKVep8j9wFULhjXz689KeT6ngEkyNHQEgoVFdkQpJxV3UsQZ4yxfPTdJKf3R7S1oiYEDqoR8nSuemwT8Jcg1zNqy26hfqY8C6XgWpp1qNvugVdfR3GXFKjwWQgRchtLbHqSzvK761EGxNEMHKKW3VjdxG96Wuvchz21M9mjLgCdroPS2QPsJdvrfv7ZAHH9xV6PnjpFwcmKSY7rJnSmiz2jMFujFqyna7vaEwDUWqeREmHG64TCY3iAMBvmH71bXDDBNobe56nWDLuDWaqAjXA58YUBQ3gxayo4spcxFgxk4nXpCMZL9hVfBfWvFC3aMUJfcY37ipPokBk93D8KBPRqPFVcMB33D61BfMHWZceJasN3VL8rVv4Ua3bRWAgTwuaQv3wrXiP1SizfbQYSnS5dimQS3bbWCWy73U1JM5GVf4oZA2TQjCKWyr3UBfhJRqV7eNoxj9bkn98RycSeYM425KncbQinWisPP9vJcNvrsyjHC1b7R7ufkMWHp1hzCvDUWBuZd1aJxuVBeqM8L2nCaT3nyEYVJbmPBM7ruqQfEu7F3n9vKkTEuFzsVQqsHAncQfyKtKsfVsyuB8JHUnwNXDCRi4DEEqce612z6gkamK2QCMBgqD1SkAJGdwhT7P5XbUYoRgzYExvZfFbSh8xSvmi5RgLvgWDYFLGXDVVbCdLPPTDJuMydmjZVmgwyBSjnLzDGYFmLzgh3DzkdJeYhbRcuPvHqfGPyUcLJRvxs2hSs4kHcycXtncJsTUgMoKdKgF3c7MoYPwAg5624zzDWXxCqYb1by11bfoYKUbCLCoJcEVzNQMDSxMKt8STBBhzawzg5mqk8trEtiPAvFA5yxC4w3yVCZB8FWNKBnQLmfnZiXZUKnkWychP3GpmSmvqFrip79WRygrzBBD1G8LFmcv6hpKQscJPnBRxUyLb6NDqVS4PzcqT3H9AQcSDKsuezmrf3Bv4eX4xU9Uzar3hXgDwyHosGfGAhBtnDtPLkpYjxCPjHWz2xejFTu3v7Aa9cwWYPb8gnoJf9HNLnihQdsM9yLeZoKRfZpNV1VMidJw49WowKbpSigc4RcB1t3iPT5Pe7vMSe4ENFQQn",
"assets": [
{
"tokenId": "b7faaa4011378055704964124706885dfb07e2966a85e946bdd02742e29ec36e",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "4d0e240008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b728",
"sigmaType": "(Coll[SByte], SLong)",
"renderedValue": "[0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7,20]"
},
"R6": {
"serializedValue": "0e20b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a",
"sigmaType": "Coll[SByte]",
"renderedValue": "b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a"
},
"R8": {
"serializedValue": "1103e8e1c60180897a80897a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1628276,1000000,1000000]"
},
"R7": {
"serializedValue": "1a00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[]"
},
"R9": {
"serializedValue": "0e9e017b227469746c65223a2254657374205633222c226465736372697074696f6e223a22222c22696d61676555524c223a22222c227765624c696e6b223a22222c22736572766963654964223a2262666165616638386165346163316265366464376164356632343766333063666339636439303336303330303035346162363132366136366663343337323466222c226d6972726f7255726c73223a5b5d7d",
"sigmaType": "Coll[SByte]",
"renderedValue": "7b227469746c65223a2254657374205633222c226465736372697074696f6e223a22222c22696d61676555524c223a22222c227765624c696e6b223a22222c22736572766963654964223a2262666165616638386165346163316265366464376164356632343766333063666339636439303336303330303035346162363132366136366663343337323466222c226d6972726f7255726c73223a5b5d7d"
},
"R4": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
}
}
},
{
"boxId": "c3682b2707f3701782906fb051309f3e7711360189071e6d0fb015da027418cf",
"value": 678107160,
"index": 1,
"spendingProof": "71aed31c4a462b45ee4c914c6f6273794f0ce3baad9d3154d4689d0ce7dd524c908847fe0249f41a87fd39eadbcc296221ae798589fbb035",
"outputBlockId": "26a253e34d413ce98abdb87dfbe8eb244706e4aaa20c58a001652bd60b35b616",
"outputTransactionId": "c045a8c340f5916ee81d4f48534a31fb64de73a9e9aa9d7cad375aee718a2d7c",
"outputIndex": 2,
"outputGlobalIndex": 50677912,
"outputCreatedAt": 1628274,
"outputSettledAt": 1628276,
"ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
"address": "9fcwctfPQPkDfHgxBns5Uu3dwWpaoywhkpLEobLuztfQuV5mt3T",
"assets": [
{
"tokenId": "cdca7d850f29ccf7bc66409ce9139229a29f8d2cdd8374263fa57dff97502216",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "8821752e5972bcf3cb98f1a19f13e7fe440cccbe4facf3a234b6b838cc70be84",
"index": 1,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 2,
"amount": 96951098,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 3,
"amount": 999899774500,
"name": "GOLD",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 4,
"amount": 1,
"name": null,
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"type": null
},
{
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"type": null
},
{
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},
{
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"index": 7,
"amount": 61056,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
},
{
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"index": 8,
"amount": 4103,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
},
{
"tokenId": "ed2197ebb2b958670cb568aeed54693617a3f3718d16d1a298b8c8d337193da0",
"index": 9,
"amount": 4103,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
},
{
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"index": 10,
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"name": "TEST DEV 50 PERCENT APT",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 11,
"amount": 10000,
"name": "TEST FULL WITHDRAW V3 APT",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 12,
"amount": 99981000,
"name": "TGD",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 13,
"amount": 7000,
"name": "Test project for 1.2 V1 APT",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 14,
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"name": "🚬",
"decimals": 0,
"type": "EIP-004"
},
{
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},
{
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"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "cb235b4a4e772450292a07ed767568ec0ccdb92c5ae9f0035eaf57f58197afad",
"value": 1000000,
"index": 0,
"outputBlockId": "317302c74b9fd10d5129cccfd0f36b30ecc40a69bb5e3afad174209c9b69c0a8",
"outputTransactionId": "060008c727406d1ac1ddcd41e680f1bfee20dc6096c8c76e5eb56c42224585ad",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "0e2096dea868f51d5a5ca4406adff99e2b5ccaed8fa6790b74217a5966d6926fc55f",
"sigmaType": "Coll[SByte]",
"renderedValue": "96dea868f51d5a5ca4406adff99e2b5ccaed8fa6790b74217a5966d6926fc55f"
},
"R6": {
"serializedValue": "0e20b7faaa4011378055704964124706885dfb07e2966a85e946bdd02742e29ec36e",
"sigmaType": "Coll[SByte]",
"renderedValue": "b7faaa4011378055704964124706885dfb07e2966a85e946bdd02742e29ec36e"
},
"R8": {
"serializedValue": "0e20c804ab362d06ede6623eb85bdf7c95d8f42f5455810365d053c355712124cda9",
"sigmaType": "Coll[SByte]",
"renderedValue": "c804ab362d06ede6623eb85bdf7c95d8f42f5455810365d053c355712124cda9"
},
"R7": {
"serializedValue": "0e20d0400cfa3b4c18f7ccc32ed9e4960d535d3fed69b7f36b31e29b6b17151d1f93",
"sigmaType": "Coll[SByte]",
"renderedValue": "d0400cfa3b4c18f7ccc32ed9e4960d535d3fed69b7f36b31e29b6b17151d1f93"
},
"R9": {
"serializedValue": "1104d8042ec80128",
"sigmaType": "Coll[SLong]",
"renderedValue": "[300,23,100,20]"
},
"R4": {
"serializedValue": "0e240008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7"
}
}
}
],
"outputs": [
{
"boxId": "103200aabb8a4bf07f38adb989eccfd271f00410e85cef2f55b6cafa0404e686",
"transactionId": "dc5073f59f78a263835902b6d29654d57dbff3f16426293d59e8d20614bc6f95",
"blockId": "28e8b32907879c69a73747ed3d050c04a8c0a56b592b914d28ecd4463d73dec6",
"value": 1000000,
"index": 0,
"globalIndex": 50677989,
"creationHeight": 1628278,
"settlementHeight": 1628279,
"ergoTree": "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",
"ergoTreeConstants": "0: 3\n1: Coll(73,50,-82,23,-85,126,-72,-71,82,-53,15,-90,33,-31,12,-20,20,-78,-91,27,66,-39,-55,-70,-65,50,-113,-115,-84,107,59,79)\n2: 0\n3: 0\n4: 1\n5: SigmaProp(ProveDlog(ECPoint(1bf847,c2be87,...)))\n6: Coll(0,8,-51)\n7: 0\n8: 0\n9: 0\n10: 3\n11: 3\n12: false\n13: 0\n14: 3\n15: 3\n16: 1\n17: 1\n18: 1\n19: 1\n20: 0\n21: 0\n22: -1\n23: false\n24: true\n25: -1\n26: 1\n27: 0\n28: true\n29: 1\n30: 0\n31: 0\n32: 1\n33: 2\n34: 2\n35: 3\n36: false\n37: false\n38: false\n39: false\n40: false\n41: 0\n42: Coll(47,118,46,-91,-45,7,77,49,21,-3,101,-98,-18,52,34,54,78,-78,106,-125,110,51,90,-38,-17,-46,-34,56,-2,-124,-102,-75)\n43: 0\n44: 0\n45: 2\n46: 1\n47: false\n48: 0\n49: 1\n50: 0\n51: Coll(-10,-127,-98,11,124,-7,-100,-116,120,114,-74,47,73,-123,-72,-39,0,-58,21,9,37,-48,30,-78,121,120,117,23,-88,72,-74,-40)\n52: 1\n53: 0\n54: 1\n55: 0\n56: 3\n57: 30\n58: -1\n59: -1\n60: false\n61: true\n62: 1\n63: false\n64: false\n65: false\n66: 0\n67: 0\n68: 0\n69: 100\n70: 5\n71: 100\n72: 1000000\n73: 1000000\n74: 0\n75: 0\n76: 0\n77: 1000000\n78: 0\n79: 0\n80: true\n81: 0\n82: true\n83: 0\n84: true\n85: false\n86: 5\n87: 100\n88: 1000000\n89: 0\n90: 0\n91: 1\n92: 0\n93: 0\n94: true\n95: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R7[Coll[Long]].get\n val l4 = coll3(placeholder[Int](0))\n val bool5 = l2 < l4\n val coll6 = placeholder[Coll[Byte]](1)\n val coll7 = SELF.tokens(placeholder[Int](2))._1\n val tuple8 = SELF.R5[(Coll[Byte], Coll[Byte])].get\n val coll9 = tuple8._2\n val l10 = coll3(placeholder[Int](3))\n val coll11 = tuple8._1\n val coll12 = SELF.R6[Coll[Coll[Byte]]].get\n val l13 = coll3(placeholder[Int](4))\n val tuple14 = SELF.R8[(Coll[Byte], Long)].get\n val l15 = tuple14._2\n val coll16 = tuple14._1\n val prop17 = placeholder[SigmaProp](5)\n val bool18 = coll9 != Coll[Byte]()\n val coll19 = placeholder[Coll[Byte]](6)\n val prop20 = if (bool18) {(\n val coll20 = INPUTS.filter({(box20: Box) => (blake2b256(box20.propositionBytes) == coll6) && (box20.R5[Coll[Byte]].get == coll9) })\n if (coll20.size > placeholder[Int](7)) {(\n val coll21 = coll20(placeholder[Int](8)).R4[Coll[Byte]].get\n sigmaProp(coll21.slice(placeholder[Int](9), placeholder[Int](10)) == coll19) && proveDlog(\n decodePoint(coll21.slice(placeholder[Int](11), coll21.size))\n ) || sigmaProp(INPUTS.exists({(box22: Box) => box22.propositionBytes == coll21 }))\n )} else { sigmaProp(placeholder[Boolean](12)) }\n )} else {\n sigmaProp(coll16.slice(placeholder[Int](13), placeholder[Int](14)) == coll19) && proveDlog(\n decodePoint(coll16.slice(placeholder[Int](15), coll16.size))\n ) || sigmaProp(INPUTS.exists({(box20: Box) => box20.propositionBytes == coll16 }))\n }\n sigmaProp(i1 == placeholder[Int](16)) && sigmaProp(if ((bool5 && (INPUTS.size > placeholder[Int](17))) && (OUTPUTS.size > placeholder[Int](18))) {(\n val coll21 = CONTEXT.dataInputs\n val coll22 = coll21.filter({(box22: Box) => ((blake2b256(box22.propositionBytes) == coll6) && (box22.R6[Coll[Byte]].get == coll7)) && (box22.R5[Coll[Byte]].get != coll9) })\n if (coll22.size == placeholder[Int](19)) {(\n val box23 = coll22(placeholder[Int](20))\n val box24 = OUTPUTS(placeholder[Int](21))\n if (((blake2b256(box23.propositionBytes) == coll6) && (box23.R6[Coll[Byte]].get == coll7)) && (box23.creationInfo._1.toLong < l10)) {(\n val tuple25 = (placeholder[Long](22), placeholder[Boolean](23))\n val l26 = box23.R9[Coll[Long]].get.fold(tuple25, {(tuple26: ((Long, Boolean), Long)) =>\n val tuple28 = tuple26._1\n val l29 = tuple26._2\n if (tuple28._2) { tuple28 } else { if (blake2b256(box23.R7[Coll[Byte]].get.append(longToByteArray(l29)).append(box23.R8[Coll[Byte]].get).append(coll11)) == box23.R5[Coll[Byte]].get) { (l29, placeholder[Boolean](24)) } else { tuple28 } }\n })._1\n val bool27 = l26 != placeholder[Long](25)\n if (bool27) {(\n val coll28 = Coll[Byte]()\n val coll29 = if (coll9 == coll28) { box23.R5[Coll[Byte]].get } else {(\n val coll29 = coll21.filter({(box29: Box) => ((blake2b256(box29.propositionBytes) == coll6) && (box29.R5[Coll[Byte]].get == coll9)) && (box29.R6[Coll[Byte]].get == coll7) })\n if (coll29.size == placeholder[Int](26)) {(\n val box30 = coll29(placeholder[Int](27))\n val l31 = box30.R9[Coll[Long]].get.fold(tuple25, {(tuple31: ((Long, Boolean), Long)) =>\n val tuple33 = tuple31._1\n val l34 = tuple31._2\n if (tuple33._2) { tuple33 } else { if (blake2b256(box30.R7[Coll[Byte]].get.append(longToByteArray(l34)).append(box30.R8[Coll[Byte]].get).append(coll11)) == box30.R5[Coll[Byte]].get) { (l34, placeholder[Boolean](28)) } else { tuple33 } }\n })._1\n if ((l26 > l31) || ((l26 == l31) && (box23.creationInfo._1 < box30.creationInfo._1))) { box23.R5[Coll[Byte]].get } else { coll28 }\n )} else { coll28 }\n )}\n if ((coll29 != coll28) && (coll29 != coll9)) { ((((((((((((box24.propositionBytes == SELF.propositionBytes) && (box24.R4[Int].get == i1)) && (box24.tokens.size == placeholder[Int](29))) && (box24.tokens(placeholder[Int](30))._1 == coll7)) && (box24.R5[(Coll[Byte], Coll[Byte])].get == (coll11, coll29))) && (box24.R6[Coll[Coll[Byte]]].get == coll12)) && (box24.R7[Coll[Long]].get(placeholder[Int](31)) == l10)) && (box24.R7[Coll[Long]].get(placeholder[Int](32)) == l13)) && (box24.R7[Coll[Long]].get(placeholder[Int](33)) == coll3(placeholder[Int](34)))) && (box24.R7[Coll[Long]].get(placeholder[Int](35)) == l4)) && (box24.R8[(Coll[Byte], Long)].get._2 == l15)) && (box24.R9[(Coll[Byte], Coll[Byte])].get == SELF.R9[(Coll[Byte], Coll[Byte])].get)) && bool27 } else { placeholder[Boolean](36) }\n )} else { placeholder[Boolean](37) }\n )} else { placeholder[Boolean](38) }\n )} else { placeholder[Boolean](39) }\n )} else { placeholder[Boolean](40) }) || sigmaProp(if (bool5 && (CONTEXT.dataInputs.size > placeholder[Int](41))) {(\n val coll21 = CONTEXT.dataInputs\n val coll22 = coll21.filter({(box22: Box) => blake2b256(box22.propositionBytes) == placeholder[Coll[Byte]](42) })\n val i23 = coll22.size\n val i24 = coll12.size\n val coll25 = OUTPUTS.filter({(box25: Box) => box25.propositionBytes == SELF.propositionBytes })\n if (if (i23 < if (i24 == placeholder[Int](43)) { placeholder[Int](44) } else { i24 / placeholder[Int](45) + placeholder[Int](46) }) { placeholder[Boolean](47) } else {(\n val coll26 = coll22.map({(box26: Box) => box26.tokens(placeholder[Int](48))._1 })\n coll26.indices.forall({(i27: Int) => !coll26.slice(i27 + placeholder[Int](49), i23).exists({(coll29: Coll[Byte]) => coll29 == coll26(i27) }) }) && coll22.forall({(box27: Box) => (coll12.exists({(coll29: Coll[Byte]) => coll29 == box27.tokens(placeholder[Int](50))._1 }) && (box27.R4[Coll[Byte]].get == placeholder[Coll[Byte]](51))) && (box27.R5[Coll[Byte]].get == coll9) })\n )} && (coll25.size == placeholder[Int](52))) {(\n val coll26 = INPUTS.filter({(box26: Box) => (blake2b256(box26.propositionBytes) == coll6) && (box26.R5[Coll[Byte]].get == coll9) })\n val box27 = coll25(placeholder[Int](53))\n if (coll26.size == placeholder[Int](54)) { (((box27.value >= SELF.value + coll26(placeholder[Int](55)).value) && (box27.R7[Coll[Long]].get(placeholder[Int](56)) >= l4 + placeholder[Long](57))) && (box27.R5[(Coll[Byte], Coll[Byte])].get._2 == coll21.filter({(box28: Box) => blake2b256(box28.propositionBytes) == coll6 }).fold((placeholder[Long](58), Coll[Byte]()), {(tuple28: ((Long, Coll[Byte]), Box)) =>\n val box30 = tuple28._2\n val coll31 = box30.R5[Coll[Byte]].get\n val tuple32 = tuple28._1\n if (coll31 != coll9) {(\n val l33 = box30.R9[Coll[Long]].get.fold((placeholder[Long](59), placeholder[Boolean](60)), {(tuple33: ((Long, Boolean), Long)) =>\n val tuple35 = tuple33._1\n val l36 = tuple33._2\n if (tuple35._2) { tuple35 } else { if (blake2b256(box30.R7[Coll[Byte]].get.append(longToByteArray(l36)).append(box30.R8[Coll[Byte]].get).append(coll11)) == coll31) { (l36, placeholder[Boolean](61)) } else { tuple35 } }\n })._1\n if (l33 > tuple32._1) { (l33, coll31) } else { tuple32 }\n )} else { tuple32 }\n })._2)) && ((box27.R4[Int].get == i1) && (i1 == placeholder[Int](62))) } else { placeholder[Boolean](63) }\n )} else { placeholder[Boolean](64) }\n )} else { placeholder[Boolean](65) }) || if ((l2 >= l4) && (OUTPUTS.size > placeholder[Int](66))) {(\n val coll21 = INPUTS.filter({(box21: Box) => blake2b256(box21.propositionBytes) == coll6 })\n val l22 = coll21.fold(placeholder[Long](67), {(tuple22: (Long, Box)) => tuple22._1 + tuple22._2.value })\n if (bool18) { if (coll21.filter({(box23: Box) => box23.R5[Coll[Byte]].get == coll9 }).size > placeholder[Int](68)) {(\n val l23 = l22 * l15 / placeholder[Long](69)\n val l24 = l22 * placeholder[Long](70) / placeholder[Long](71)\n val bool25 = l22 - l23 - l24 >= placeholder[Long](72)\n val l26 = if (bool25) { l13 + l23 } else { l13 }\n val l27 = l26 - if ((l26 < placeholder[Long](73)) && (l26 > placeholder[Long](74))) { l26 } else { placeholder[Long](75) }\n val l28 = if (bool25) { l24 } else { placeholder[Long](76) }\n val l29 = l28 - if ((l28 < placeholder[Long](77)) && (l28 > placeholder[Long](78))) { l28 } else { placeholder[Long](79) }\n prop20 && sigmaProp((placeholder[Boolean](80) && if (l27 > placeholder[Long](81)) { OUTPUTS.exists({(box30: Box) => (box30.value >= l27) && (box30.propositionBytes == coll16) }) } else { placeholder[Boolean](82) }) && if (l29 > placeholder[Long](83)) { OUTPUTS.exists({(box30: Box) => (box30.value >= l29) && (box30.propositionBytes == prop17.propBytes) }) } else { placeholder[Boolean](84) })\n )} else { sigmaProp(placeholder[Boolean](85)) } } else {(\n val l23 = l22 * placeholder[Long](86) / placeholder[Long](87)\n val l24 = l23 - if ((l23 < placeholder[Long](88)) && (l23 > placeholder[Long](89))) { l23 } else { placeholder[Long](90) }\n prop20 && sigmaProp(\n OUTPUTS.exists(\n {(box25: Box) =>\n (((box25.value >= l22 + l13 - l24) && (box25.propositionBytes == coll16)) && (box25.tokens.size == placeholder[Int](91))) && (\n box25.tokens(placeholder[Int](92))._1 == coll7\n )\n }\n ) && if (l24 > placeholder[Long](93)) { OUTPUTS.exists({(box25: Box) => (box25.value >= l24) && (box25.propositionBytes == prop17.propBytes) }) } else {\n placeholder[Boolean](94)\n }\n )\n )}\n )} else { sigmaProp(placeholder[Boolean](95)) }\n}",
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"sigmaType": "Coll[SLong]",
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{
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