Transaction
ID: 8c479bf072...9d2d
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.94988528 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
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:
0.94878528 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 69,943
Total coins transferred: 0.95088528 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000241 ERG
Raw Transaction Data
{
"id": "8c479bf07284616704f697de86dcf2bdd3e205e80e060ad6bd21c1258d099d2d",
"blockId": "8ccc1d9d911acd4bf74d75584b9318b877c01f32b4e937c67847f0406cfa53ec",
"inclusionHeight": 1696845,
"timestamp": 1768061216966,
"index": 9,
"globalIndex": 10122829,
"numConfirmations": 69943,
"inputs": [
{
"boxId": "962e5cda0b8ddf1de6cf8fe04a244cdaea6a3f76fdc66b639b4e11be788dc5d2",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "5607dcff9087eaeeb6ee7f17cd112f09d186eac7dfe9f826819e4ce9e7bfad2b",
"outputTransactionId": "7b1fea3b8c26bfb7e6c0cbe57dd0b4fb68b81f09598abd9aa0fc4ed70399ab9b",
"outputIndex": 0,
"outputGlobalIndex": 52883357,
"outputCreatedAt": 1696838,
"outputSettledAt": 1696841,
"ergoTree": "19d30a3804000e20e8e3103f08c7447a7b8480e39ff944d75bda819d89848b8d9a30c1a1c83a9c830400040204040500040204000402040001010e2003774b575f9e1d9931fe9884473176de6d13acc7c2881ef86f4a859bfaec1db20402040001000101051401000e203a94621862f67454cbdd613ed3a64482b9dfe3093c6182356ba4f4a14411f79504000e208299d98e15ebee7fa39ad716de7c8bb191790a1bf4b7c3f91af35a0e3618770604000400040204020400040204040406040604080408040a050a0400040004020406040201000100010004040400050a0e209b0365253219b1b732006bf3afe66ece98cfd6132c2a77d74a51e9a808de3f7a050204020404053c01000400040004000580897a0100d810d601e4c6a70404d6027ea305d603e4c6a70811d604b27203730000d6057301d606e4c6a7060ed6078cb2db6308a773020001d608e4c6a7054d0ed6098c720801d60ae4c6a7091ad60bb2720a730300d60cb27203730400d60dd9010d63b0b5db6308720dd9010f4d0e938c720f01720b7305d9010f414d0e9a8c720f018c8c720f0202d60eb27203730600d60fe4c6a7071ad6108c720802d1ed9372017307ecec959272027204d801d611b5a5d901116393cbc2721172059593b172117308d805d612b27211730900d613e4c67212063c0e0ed6148c721301d6158c721302d61683000295eded93cb7214720693cbc272127205959372157216730ad801d617b5db6501fed9011763eded93cbc27217730b93e4c67217060e720793e4c67217050e72159593b17217730cd802d618b27217730d00d619e4c672180911edededb07219730ed9011a3d05d801d61c8c721a0195721c721c9593cbb3b3b3b3b3e4c67218070e72097a8c721a02e4c67218080ee4c67218040e7214e4c67218050e730f721c9593720b721692c17218720caedb63087218d9011a4d0eed938c721a01720b928c721a02720c8f7e8cc7721801057204907eb172190573107311d802d617b5db6501fed9011763edededededed93cbc27217731291b1db63087217731393e4c67217040e731493e4c67217050e7207e4c672170601e4c672170801ae720fd901190e9372198cb2db6308721773150001d618ad7217d90118638cb2db6308721873160001edededededededededededededed92da720d017212720e93b1b5db63087212d901194d0e938c7219017207731793e4c672120404731893e4c67212050e720993e4c67212071a720f93b2e4c672120811731900720493b2e4c672120811731a00720e93b2e4c672120811731b00720c93b2e4c672120811731c00b27203731d0092b2e4c672120811731e00b27203731f0092b2e4c6721208117320009a7202732193b2e4c67212091a732200b2720a73230093b2e4c67212091a732400720b93b1e4c67212091a7325afdb0c0e7218d9011904efaeb472189a72197326b17217d9011b0e93721bb2721872190073277328732995ed8f7202720492b1a5732ad802d611b2a5732b00d61299720e9d720e732cedededededededed93cbc27211732d92da720d017211721293b1b5db63087211d901134d0eed938c7213017207938c721302732e732f93e4c672110404733092e4c6721105059a7202733193cbe4c67211060e720693e4c672110705721293e4c672110805720493e4c67211091a720a733295ed8f7202721091b1a57333d803d611b2b5a5d901116393cbc27211cbc2a7733400d612c17211d613e4c67211054d0eedededededededed938cb2db63087211733500017207ed9272127336937212c1a7938c721301cbb37209c5a7938c721302721093e4c672110404720193e4c67211060e720693e4c67211071a720f93e4c672110811720393e4c67211091a720a7337",
"ergoTreeConstants": "0: 0\n1: Coll(-24,-29,16,63,8,-57,68,122,123,-124,-128,-29,-97,-7,68,-41,91,-38,-127,-99,-119,-124,-117,-115,-102,48,-63,-95,-56,58,-100,-125)\n2: 0\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 1\n9: 0\n10: true\n11: Coll(3,119,75,87,95,-98,29,-103,49,-2,-104,-124,71,49,118,-34,109,19,-84,-57,-62,-120,30,-8,111,74,-123,-101,-6,-20,29,-78)\n12: 1\n13: 0\n14: false\n15: true\n16: 10\n17: false\n18: Coll(58,-108,98,24,98,-10,116,84,-53,-35,97,62,-45,-90,68,-126,-71,-33,-29,9,60,97,-126,53,107,-92,-12,-95,68,17,-9,-107)\n19: 0\n20: Coll(-126,-103,-39,-114,21,-21,-18,127,-93,-102,-41,22,-34,124,-117,-79,-111,121,10,27,-12,-73,-61,-7,26,-13,90,14,54,24,119,6)\n21: 0\n22: 0\n23: 1\n24: 1\n25: 0\n26: 1\n27: 2\n28: 3\n29: 3\n30: 4\n31: 4\n32: 5\n33: 5\n34: 0\n35: 0\n36: 1\n37: 3\n38: 1\n39: false\n40: false\n41: false\n42: 2\n43: 0\n44: 5\n45: Coll(-101,3,101,37,50,25,-79,-73,50,0,107,-13,-81,-26,110,-50,-104,-49,-42,19,44,42,119,-41,74,81,-23,-88,8,-34,63,122)\n46: 1\n47: 1\n48: 2\n49: 30\n50: false\n51: 0\n52: 0\n53: 0\n54: 1000000\n55: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R8[Coll[Long]].get\n val l4 = coll3(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n val coll6 = SELF.R6[Coll[Byte]].get\n val coll7 = SELF.tokens(placeholder[Int](2))._1\n val tuple8 = SELF.R5[(Coll[Byte], Long)].get\n val coll9 = tuple8._1\n val coll10 = SELF.R9[Coll[Coll[Byte]]].get\n val coll11 = coll10(placeholder[Int](3))\n val l12 = coll3(placeholder[Int](4))\n val func13 = {(box13: Box) =>\n box13.tokens.filter({(tuple15: (Coll[Byte], Long)) => tuple15._1 == coll11 }).fold(\n placeholder[Long](5), {(tuple15: (Long, (Coll[Byte], Long))) => tuple15._1 + tuple15._2._2 }\n )\n }\n val l14 = coll3(placeholder[Int](6))\n val coll15 = SELF.R7[Coll[Coll[Byte]]].get\n val l16 = tuple8._2\n sigmaProp((i1 == placeholder[Int](7)) && ((if (l2 >= l4) {(\n val coll17 = OUTPUTS.filter({(box17: Box) => blake2b256(box17.propositionBytes) == coll5 })\n if (coll17.size == placeholder[Int](8)) {(\n val box18 = coll17(placeholder[Int](9))\n val tuple19 = box18.R6[(Coll[Byte], Coll[Byte])].get\n val coll20 = tuple19._1\n val coll21 = tuple19._2\n val coll22 = Coll[Byte]()\n if (((blake2b256(coll20) == coll6) && (blake2b256(box18.propositionBytes) == coll5)) && if (coll21 == coll22) { placeholder[Boolean](10) } else {(\n val coll23 = CONTEXT.dataInputs.filter({(box23: Box) => ((blake2b256(box23.propositionBytes) == placeholder[Coll[Byte]](11)) && (box23.R6[Coll[Byte]].get == coll7)) && (box23.R5[Coll[Byte]].get == coll21) })\n if (coll23.size == placeholder[Int](12)) {(\n val box24 = coll23(placeholder[Int](13))\n val coll25 = box24.R9[Coll[Long]].get\n ((coll25.fold(placeholder[Boolean](14), {(tuple26: (Boolean, Long)) =>\n val bool28 = tuple26._1\n if (bool28) { bool28 } else { if (blake2b256(box24.R7[Coll[Byte]].get.append(coll9).append(longToByteArray(tuple26._2)).append(box24.R8[Coll[Byte]].get).append(box24.R4[Coll[Byte]].get).append(coll20)) == box24.R5[Coll[Byte]].get) { placeholder[Boolean](15) } else { bool28 } }\n }) && if (coll11 == coll22) { box24.value >= l12 } else { box24.tokens.exists({(tuple26: (Coll[Byte], Long)) => (tuple26._1 == coll11) && (tuple26._2 >= l12) }) }) && (box24.creationInfo._1.toLong < l4)) && (coll25.size.toLong <= placeholder[Long](16))\n )} else { placeholder[Boolean](17) }\n )}) {(\n val coll23 = CONTEXT.dataInputs.filter({(box23: Box) => ((((((blake2b256(box23.propositionBytes) == placeholder[Coll[Byte]](18)) && (box23.tokens.size > placeholder[Int](19))) && (box23.R4[Coll[Byte]].get == placeholder[Coll[Byte]](20))) && (box23.R5[Coll[Byte]].get == coll7)) && box23.R6[Boolean].get) && box23.R8[Boolean].get) && coll15.exists({(coll25: Coll[Byte]) => coll25 == box23.tokens(placeholder[Int](21))._1 }) })\n val coll24 = coll23.map({(box24: Box) => box24.tokens(placeholder[Int](22))._1 })\n ((((((((((((((func13(box18) >= l14) && (box18.tokens.filter({(tuple25: (Coll[Byte], Long)) => tuple25._1 == coll7 }).size == placeholder[Int](23))) && (box18.R4[Int].get == placeholder[Int](24))) && (box18.R5[Coll[Byte]].get == coll9)) && (box18.R7[Coll[Coll[Byte]]].get == coll15)) && (box18.R8[Coll[Long]].get(placeholder[Int](25)) == l4)) && (box18.R8[Coll[Long]].get(placeholder[Int](26)) == l14)) && (box18.R8[Coll[Long]].get(placeholder[Int](27)) == l12)) && (box18.R8[Coll[Long]].get(placeholder[Int](28)) == coll3(placeholder[Int](29)))) && (box18.R8[Coll[Long]].get(placeholder[Int](30)) >= coll3(placeholder[Int](31)))) && (box18.R8[Coll[Long]].get(placeholder[Int](32)) >= l2 + placeholder[Long](33))) && (box18.R9[Coll[Coll[Byte]]].get(placeholder[Int](34)) == coll10(placeholder[Int](35)))) && (box18.R9[Coll[Coll[Byte]]].get(placeholder[Int](36)) == coll11)) && (box18.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](37))) && coll24.indices.forall({(i25: Int) => !coll24.slice(i25 + placeholder[Int](38), coll23.size).exists({(coll27: Coll[Byte]) => coll27 == coll24(i25) }) })\n )} else { placeholder[Boolean](39) }\n )} else { placeholder[Boolean](40) }\n )} else { placeholder[Boolean](41) } || if ((l2 < l4) && (OUTPUTS.size >= placeholder[Int](42))) {(\n val box17 = OUTPUTS(placeholder[Int](43))\n val l18 = l14 - l14 / placeholder[Long](44)\n ((((((((blake2b256(box17.propositionBytes) == placeholder[Coll[Byte]](45)) && (func13(box17) >= l18)) && (box17.tokens.filter({(tuple19: (Coll[Byte], Long)) => (tuple19._1 == coll7) && (tuple19._2 == placeholder[Long](46)) }).size == placeholder[Int](47))) && (box17.R4[Int].get == placeholder[Int](48))) && (box17.R5[Long].get >= l2 + placeholder[Long](49))) && (blake2b256(box17.R6[Coll[Byte]].get) == coll6)) && (box17.R7[Long].get == l18)) && (box17.R8[Long].get == l4)) && (box17.R9[Coll[Coll[Byte]]].get == coll10)\n )} else { placeholder[Boolean](50) }) || if ((l2 < l16) && (OUTPUTS.size > placeholder[Int](51))) {(\n val box17 = OUTPUTS.filter({(box17: Box) => blake2b256(box17.propositionBytes) == blake2b256(SELF.propositionBytes) })(placeholder[Int](52))\n val l18 = box17.value\n val tuple19 = box17.R5[(Coll[Byte], Long)].get\n ((((((((box17.tokens(placeholder[Int](53))._1 == coll7) && ((l18 >= placeholder[Long](54)) && (l18 == SELF.value))) && (tuple19._1 == blake2b256(coll9.append(SELF.id)))) && (tuple19._2 == l16)) && (box17.R4[Int].get == i1)) && (box17.R6[Coll[Byte]].get == coll6)) && (box17.R7[Coll[Coll[Byte]]].get == coll15)) && (box17.R8[Coll[Long]].get == coll3)) && (box17.R9[Coll[Coll[Byte]]].get == coll10)\n )} else { placeholder[Boolean](55) }))\n}",
"address": "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",
"assets": [
{
"tokenId": "6ffc9d6676e47056b24e6cd70de104a1727e5f74623d4a7a20c0b8ff3f3b423d",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 1,
"amount": 500,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "4d0e087870a5d6e23a49c58e91cf01",
"sigmaType": "(Coll[SByte], SLong)",
"renderedValue": "[7870a5d6e23a49c5,1696839]"
},
"R6": {
"serializedValue": "0e20b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a",
"sigmaType": "Coll[SByte]",
"renderedValue": "b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a"
},
"R8": {
"serializedValue": "11069691cf01e807c80100a0c21e14",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1696843,500,100,0,250000,10]"
},
"R7": {
"serializedValue": "1a00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[]"
},
"R9": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[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,aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71]"
},
"R4": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
}
}
},
{
"boxId": "1292a92f7548053acb142fcf20adf06c18c8d4febdddc5484a4c9577f343c9da",
"value": 949885280,
"index": 1,
"spendingProof": "79d6da4294b5a84960020bb39fae78d177e58805594c5c8334022e31abadb110c451438acd7c80907f0075f3363c01a9a6fffe0786ff7dfd",
"outputBlockId": "cccb0ceaa3fbbb0631fa75cdda4df2b5e3aff3885c9b8366bde0946e664d4cad",
"outputTransactionId": "6b7244467c73104b1524bff6a66d3c7fca70bac57cc353a408547342377f8104",
"outputIndex": 2,
"outputGlobalIndex": 52883432,
"outputCreatedAt": 1696841,
"outputSettledAt": 1696843,
"ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
"address": "9fcwctfPQPkDfHgxBns5Uu3dwWpaoywhkpLEobLuztfQuV5mt3T",
"assets": [
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 0,
"amount": 95829498,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "532a61b93c9c3f02b8e81afddb1f72badab84696634fd2340ecab557dc36524e",
"index": 1,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "9c17dccbdea7041f524315bbdba68a04c7d9fa05961d87705f7cc4a455ccaaa7",
"index": 2,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "a6b3df8edc3223975b49247b425e69a85cb45f3c7a94668ba89c890f2f0d2194",
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"ergoTree": "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",
"ergoTreeConstants": "0: 5\n1: Coll(3,119,75,87,95,-98,29,-103,49,-2,-104,-124,71,49,118,-34,109,19,-84,-57,-62,-120,30,-8,111,74,-123,-101,-6,-20,29,-78)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 2\n7: -1\n8: false\n9: true\n10: 6\n11: 1\n12: 3\n13: 4\n14: 1\n15: 1\n16: 1\n17: 1\n18: 0\n19: 0\n20: 10\n21: -1\n22: 1\n23: 0\n24: -1\n25: 0\n26: 1\n27: 0\n28: 1\n29: 2\n30: 3\n31: 4\n32: 5\n33: 6\n34: 0\n35: 0\n36: 1\n37: 2\n38: 2\n39: 5\n40: 5\n41: 3\n42: false\n43: false\n44: false\n45: false\n46: false\n47: 0\n48: Coll(58,-108,98,24,98,-10,116,84,-53,-35,97,62,-45,-90,68,-126,-71,-33,-29,9,60,97,-126,53,107,-92,-12,-95,68,17,-9,-107)\n49: 0\n50: 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)\n51: 0\n52: 0\n53: 1\n54: 0\n55: 0\n56: 2\n57: 1\n58: 1\n59: 0\n60: true\n61: 1\n62: 0\n63: 10\n64: false\n65: 1\n66: 5\n67: 0\n68: 5\n69: 0\n70: 1\n71: 0\n72: 1\n73: 2\n74: 3\n75: 4\n76: 0\n77: 6\n78: false\n79: false\n80: false\n81: 0\n82: Coll(-29,5,121,27,-29,41,77,-63,27,86,20,61,-48,-84,95,28,89,95,-71,17,81,-13,-95,93,90,99,11,44,-100,-82,-46,-52)\n83: 1\n84: 0\n85: 0\n86: 1\n87: 0\n88: 1\n89: 2\n90: 3\n91: 4\n92: 5\n93: 6\n94: false\n95: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R8[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.R6[(Coll[Byte], Coll[Byte])].get\n val coll9 = tuple8._2\n val l10 = coll3(placeholder[Int](3))\n val coll11 = SELF.R9[Coll[Coll[Byte]]].get\n val coll12 = coll11(placeholder[Int](4))\n val func13 = {(box13: Box) =>\n box13.tokens.filter({(tuple15: (Coll[Byte], Long)) => tuple15._1 == coll12 }).fold(\n placeholder[Long](5), {(tuple15: (Long, (Coll[Byte], Long))) => tuple15._1 + tuple15._2._2 }\n )\n }\n val l14 = coll3(placeholder[Int](6))\n val coll15 = SELF.R5[Coll[Byte]].get\n val coll16 = tuple8._1\n val func17 = {(box17: Box) => box17.R9[Coll[Long]].get.fold((placeholder[Long](7), placeholder[Boolean](8)), {(tuple19: ((Long, Boolean), Long)) =>\n val tuple21 = tuple19._1\n val l22 = tuple19._2\n if (tuple21._2) { tuple21 } else { if (blake2b256(box17.R7[Coll[Byte]].get.append(coll15).append(longToByteArray(l22)).append(box17.R8[Coll[Byte]].get).append(box17.R4[Coll[Byte]].get).append(coll16)) == box17.R5[Coll[Byte]].get) { (l22, placeholder[Boolean](9)) } else { tuple21 } }\n }) }\n val l18 = coll3(placeholder[Int](10))\n val coll19 = SELF.R7[Coll[Coll[Byte]]].get\n val l20 = coll3(placeholder[Int](11))\n val l21 = coll3(placeholder[Int](12))\n val l22 = coll3(placeholder[Int](13))\n sigmaProp(i1 == placeholder[Int](14)) && sigmaProp(if ((bool5 && (INPUTS.size > placeholder[Int](15))) && (OUTPUTS.size > placeholder[Int](16))) {(\n val coll23 = CONTEXT.dataInputs\n val coll24 = coll23.filter({(box24: Box) => ((blake2b256(box24.propositionBytes) == coll6) && (box24.R6[Coll[Byte]].get == coll7)) && (box24.R5[Coll[Byte]].get != coll9) })\n if (coll24.size == placeholder[Int](17)) {(\n val box25 = coll24(placeholder[Int](18))\n val box26 = OUTPUTS(placeholder[Int](19))\n if (((((blake2b256(box25.propositionBytes) == coll6) && (box25.R6[Coll[Byte]].get == coll7)) && (box25.creationInfo._1.toLong < l10)) && (func13(box25) >= l14)) && (box25.R9[Coll[Long]].get.size.toLong <= placeholder[Long](20))) {(\n val l27 = func17(box25)._1\n val bool28 = l27 != placeholder[Long](21)\n if (bool28) {(\n val coll29 = Coll[Byte]()\n val coll30 = if (coll9 == coll29) { box25.R5[Coll[Byte]].get } else {(\n val coll30 = coll23.filter({(box30: Box) => ((blake2b256(box30.propositionBytes) == coll6) && (box30.R5[Coll[Byte]].get == coll9)) && (box30.R6[Coll[Byte]].get == coll7) })\n if (coll30.size == placeholder[Int](22)) {(\n val box31 = coll30(placeholder[Int](23))\n val tuple32 = func17(box31)\n val l33 = tuple32._1\n if (tuple32._2 && (l33 != placeholder[Long](24))) {(\n val l34 = l18 + l10\n val i35 = box25.creationInfo._1\n val l36 = l27 * l34 - i35.toLong\n val i37 = box31.creationInfo._1\n val l38 = l33 * l34 - i37.toLong\n if ((l36 > l38) || ((l36 == l38) && (i35 < i37))) { box25.R5[Coll[Byte]].get } else { coll29 }\n )} else { coll29 }\n )} else { coll29 }\n )}\n if ((coll30 != coll29) && (coll30 != coll9)) { (((((((((((((((((((func13(box26) >= func13(SELF)) && (box26.tokens(placeholder[Int](25))._1 == coll7)) && (box26.R4[Int].get == i1)) && (i1 == placeholder[Int](26))) && (box26.R5[Coll[Byte]].get == coll15)) && (box26.R6[(Coll[Byte], Coll[Byte])].get._1 == coll16)) && (box26.R6[(Coll[Byte], Coll[Byte])].get._2 == coll30)) && (box26.R7[Coll[Coll[Byte]]].get == coll19)) && (box26.R8[Coll[Long]].get(placeholder[Int](27)) == l10)) && (box26.R8[Coll[Long]].get(placeholder[Int](28)) == l20)) && (box26.R8[Coll[Long]].get(placeholder[Int](29)) == l14)) && (box26.R8[Coll[Long]].get(placeholder[Int](30)) == l21)) && (box26.R8[Coll[Long]].get(placeholder[Int](31)) == l22)) && (box26.R8[Coll[Long]].get(placeholder[Int](32)) == l4)) && (box26.R8[Coll[Long]].get(placeholder[Int](33)) == l18)) && (box26.R9[Coll[Coll[Byte]]].get(placeholder[Int](34)) == coll11(placeholder[Int](35)))) && (box26.R9[Coll[Coll[Byte]]].get(placeholder[Int](36)) == coll12)) && ((box26.R9[Coll[Coll[Byte]]].get(placeholder[Int](37)) == coll11(placeholder[Int](38))) || (l4 - placeholder[Long](39) + placeholder[Long](40) < l2))) && (box26.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](41))) && bool28 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n )} else { placeholder[Boolean](44) }\n )} else { placeholder[Boolean](45) }\n )} else { placeholder[Boolean](46) }) || sigmaProp(if (bool5 && (CONTEXT.dataInputs.size > placeholder[Int](47))) {(\n val coll23 = CONTEXT.dataInputs\n val coll24 = coll23.filter({(box24: Box) => ((((((blake2b256(box24.propositionBytes) == placeholder[Coll[Byte]](48)) && (box24.tokens.size > placeholder[Int](49))) && (box24.R4[Coll[Byte]].get == placeholder[Coll[Byte]](50))) && (box24.R5[Coll[Byte]].get == coll9)) && box24.R6[Boolean].get) && (!box24.R8[Boolean].get)) && coll19.exists({(coll26: Coll[Byte]) => coll26 == box24.tokens(placeholder[Int](51))._1 }) })\n val coll25 = coll24.map({(box25: Box) => box25.tokens(placeholder[Int](52))._1 })\n val i26 = coll24.size\n val i27 = coll19.size\n val coll28 = OUTPUTS.filter({(box28: Box) => box28.propositionBytes == SELF.propositionBytes })\n if ((coll25.indices.forall({(i29: Int) => !coll25.slice(i29 + placeholder[Int](53), i26).exists({(coll31: Coll[Byte]) => coll31 == coll25(i29) }) }) && (i26 >= if (i27 == placeholder[Int](54)) { placeholder[Int](55) } else { i27 / placeholder[Int](56) + placeholder[Int](57) })) && (coll28.size == placeholder[Int](58))) {(\n val box29 = coll28(placeholder[Int](59))\n val coll30 = box29.R6[(Coll[Byte], Coll[Byte])].get._2\n val coll31 = INPUTS.filter({(box31: Box) => (blake2b256(box31.propositionBytes) == coll6) && (box31.R5[Coll[Byte]].get == coll9) })\n if (if (coll30 == Coll[Byte]()) { placeholder[Boolean](60) } else {(\n val coll32 = coll23.filter({(box32: Box) => ((blake2b256(box32.propositionBytes) == coll6) && (box32.R6[Coll[Byte]].get == coll7)) && (box32.R5[Coll[Byte]].get == coll30) })\n if (coll32.size == placeholder[Int](61)) {(\n val box33 = coll32(placeholder[Int](62))\n ((func17(box33)._2 && (func13(box33) >= l14)) && (box33.creationInfo._1.toLong < l10)) && (box33.R9[Coll[Long]].get.size.toLong <= placeholder[Long](63))\n )} else { placeholder[Boolean](64) }\n )} && (coll31.size == placeholder[Int](65))) {(\n val coll32 = box29.R8[Coll[Long]].get\n val l33 = coll32(placeholder[Int](66))\n ((func13(box29) >= func13(SELF) + func13(coll31(placeholder[Int](67)))) && (l33 >= l2 + placeholder[Long](68))) && (((((((((((((box29.tokens(placeholder[Int](69))._1 == coll7) && (box29.R4[Int].get == i1)) && (i1 == placeholder[Int](70))) && (box29.R5[Coll[Byte]].get == coll15)) && (box29.R7[Coll[Coll[Byte]]].get == coll19)) && (coll32(placeholder[Int](71)) == l10)) && (coll32(placeholder[Int](72)) == l20)) && (coll32(placeholder[Int](73)) == l14)) && (coll32(placeholder[Int](74)) == l21 + l22)) && (coll32(placeholder[Int](75)) == placeholder[Long](76))) && (l33 == l4)) && (coll32(placeholder[Int](77)) == l18)) && (box29.R9[Coll[Coll[Byte]]].get == coll11))\n )} else { placeholder[Boolean](78) }\n )} else { placeholder[Boolean](79) }\n )} else { placeholder[Boolean](80) }) || if ((l2 >= l4) && (OUTPUTS.size > placeholder[Int](81))) {(\n val coll23 = OUTPUTS.filter({(box23: Box) => blake2b256(box23.propositionBytes) == placeholder[Coll[Byte]](82) })\n if (coll23.size == placeholder[Int](83)) {(\n val box24 = coll23(placeholder[Int](84))\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((box24.tokens(placeholder[Int](85))._1 == coll7) && (box24.R4[Int].get == i1)) && (i1 == placeholder[Int](86))) && (\n box24.R5[Coll[Byte]].get == coll15\n )\n ) && (box24.R6[(Coll[Byte], Coll[Byte])].get._1 == coll16)\n ) && (box24.R6[(Coll[Byte], Coll[Byte])].get._2 == coll9)\n ) && (box24.R7[Coll[Coll[Byte]]].get == coll19)\n ) && (box24.R8[Coll[Long]].get(placeholder[Int](87)) == l10)\n ) && (box24.R8[Coll[Long]].get(placeholder[Int](88)) == l20)\n ) && (box24.R8[Coll[Long]].get(placeholder[Int](89)) == l14)\n ) && (box24.R8[Coll[Long]].get(placeholder[Int](90)) == l21)\n ) && (box24.R8[Coll[Long]].get(placeholder[Int](91)) == l22)\n ) && (box24.R8[Coll[Long]].get(placeholder[Int](92)) == l4)\n ) && (box24.R8[Coll[Long]].get(placeholder[Int](93)) == l18)\n ) && (box24.R9[Coll[Coll[Byte]]].get == coll11)\n ) && (func13(box24) >= func13(SELF))\n )\n )} else { sigmaProp(placeholder[Boolean](94)) }\n )} else { sigmaProp(placeholder[Boolean](95)) }\n}",
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"additionalRegisters": {
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},
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{
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