Transaction
ID: e560abdf91...19f3
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00109908 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.55196588 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00109908 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.55086588 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 59,953
Total coins transferred: 0.55306496 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000204 ERG
Raw Transaction Data
{
"id": "e560abdf918190d513bb82deffe547eba19b07021da6b6f8d6112963d16e19f3",
"blockId": "6aeb10a44217e71782be9b7a10b25a8442a969c3104831f639d7b42edd554481",
"inclusionHeight": 1716154,
"timestamp": 1770394501359,
"index": 7,
"globalIndex": 10262010,
"numConfirmations": 59953,
"inputs": [
{
"boxId": "4f00f2ffa9fba3b89b285df33c35ba22db27a6ed8b1ecd87d998e33c241cb93a",
"value": 1099080,
"index": 0,
"spendingProof": null,
"outputBlockId": "b3c90ee1e4b74394110d267e361916ce0a27c774ae2dbb8d4f369906fae8fc37",
"outputTransactionId": "8c94e6b970942b401f290caa5aaebf8f19ca2f90747b31bb6203d55c403a9e6f",
"outputIndex": 0,
"outputGlobalIndex": 53424436,
"outputCreatedAt": 1716138,
"outputSettledAt": 1716141,
"ergoTree": "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",
"ergoTreeConstants": "0: 2\n1: Coll(-5,-4,-62,-115,-117,-94,76,64,118,0,15,50,84,-80,104,93,-64,-66,70,8,-15,-62,76,27,-107,-22,22,-72,45,34,41,32)\n2: 0\n3: 1\n4: 4\n5: 0\n6: 5\n7: 0\n8: 3\n9: 0\n10: Coll(-102,-33,117,-96,-58,-111,-107,78,-112,-118,-18,-109,59,39,-4,75,81,-128,79,22,-54,-75,-47,-30,38,79,88,26,-68,-21,23,3)\n11: 0\n12: 90\n13: 1\n14: 0\n15: true\n16: Coll(45,-126,27,3,-30,-34,114,118,-69,-21,-77,-1,65,-20,55,79,-99,110,-38,67,100,97,-111,76,1,38,-126,-49,100,95,-92,-54)\n17: 1\n18: 0\n19: false\n20: true\n21: Coll(122,-94,-75,-37,-122,16,-18,-68,-23,35,110,21,-55,109,-47,84,-91,113,115,65,96,4,98,-91,-79,-37,114,2,-73,30,-45,38)\n22: 0\n23: 0\n24: 1\n25: 10\n26: false\n27: 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)\n28: 0\n29: 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)\n30: 0\n31: 0\n32: 1\n33: 1\n34: 0\n35: 1\n36: 1\n37: 2\n38: 3\n39: 4\n40: 5\n41: 5\n42: 6\n43: 6\n44: 7\n45: 7\n46: 8\n47: 5\n48: 0\n49: 1\n50: 2\n51: 2\n52: 4\n53: 1\n54: false\n55: false\n56: false\n57: 1\n58: 0\n59: 5\n60: 0\n61: 2\n62: 30\n63: 2\n64: 0\n65: 1\n66: false\n67: 1\n68: 0\n69: 0\n70: 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 coll8 = CONTEXT.dataInputs\n val coll9 = SELF.R5[Coll[Byte]].get\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 l13 = coll3(placeholder[Int](5))\n val l14 = l4 - placeholder[Long](6)\n val func15 = {(box15: Box) =>\n box15.tokens.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 == coll11 }).fold(\n placeholder[Long](7), {(tuple17: (Long, (Coll[Byte], Long))) => tuple17._1 + tuple17._2._2 }\n )\n }\n val coll16 = SELF.R7[Coll[Coll[Byte]]].get\n val l17 = coll3(placeholder[Int](8))\n val coll18 = coll10(placeholder[Int](9))\n val coll19 = OUTPUTS.filter({(box19: Box) => blake2b256(box19.propositionBytes) == placeholder[Coll[Byte]](10) })\n val coll20 = OUTPUTS.filter({(box20: Box) => blake2b256(box20.propositionBytes) == blake2b256(SELF.propositionBytes) })\n sigmaProp((i1 == placeholder[Int](11)) && ((if ((l2 >= l4) && (l2 < l4 + placeholder[Long](12))) {(\n val coll21 = OUTPUTS.filter({(box21: Box) => blake2b256(box21.propositionBytes) == coll5 })\n if (coll21.size == placeholder[Int](13)) {(\n val box22 = coll21(placeholder[Int](14))\n val tuple23 = box22.R6[(Coll[Byte], Coll[Byte])].get\n val coll24 = tuple23._1\n val coll25 = tuple23._2\n val coll26 = Coll[Byte]()\n if (((blake2b256(coll24) == coll6) && (blake2b256(box22.propositionBytes) == coll5)) && if (coll25 == coll26) { placeholder[Boolean](15) } else {(\n val coll27 = coll8.filter({(box27: Box) => ((blake2b256(box27.propositionBytes) == placeholder[Coll[Byte]](16)) && (box27.R6[Coll[Byte]].get == coll7)) && (box27.R5[Coll[Byte]].get == coll25) })\n if (coll27.size == placeholder[Int](17)) {(\n val box28 = coll27(placeholder[Int](18))\n val coll29 = box28.R9[Coll[Long]].get\n (((coll29.fold(placeholder[Boolean](19), {(tuple30: (Boolean, Long)) =>\n val bool32 = tuple30._1\n if (bool32) { bool32 } else { if (blake2b256(box28.R7[Coll[Byte]].get.append(coll9).append(longToByteArray(tuple30._2)).append(box28.R8[Coll[Byte]].get).append(box28.R4[Coll[Byte]].get).append(coll24)) == box28.R5[Coll[Byte]].get) { placeholder[Boolean](20) } else { bool32 } }\n }) && if (coll11 == coll26) { box28.value >= l12 } else { box28.tokens.exists({(tuple30: (Coll[Byte], Long)) => (tuple30._1 == coll11) && (tuple30._2 >= l12) }) }) && ({(box30: Box) =>\n val coll32 = coll8.filter({(box32: Box) =>\n val opt34 = box32.R4[Coll[Byte]]\n (opt34.isDefined && (opt34.get == box30.R7[Coll[Byte]].get)) && (blake2b256(box32.propositionBytes) == placeholder[Coll[Byte]](21))\n })\n if (coll32.size > placeholder[Int](22)) {(\n val l33 = coll32.fold(coll32(placeholder[Int](23)), {(tuple33: (Box, Box)) =>\n val box35 = tuple33._2\n val box36 = tuple33._1\n if (box35.creationInfo._1 < box36.creationInfo._1) { box35 } else { box36 }\n }).creationInfo._1.toLong\n if (l33 < l13) { l13 } else { l33 }\n )} else { l4 }\n }(box28) < l14 - placeholder[Long](24))) && (box28.creationInfo._1.toLong < l4)) && (coll29.size.toLong <= placeholder[Long](25))\n )} else { placeholder[Boolean](26) }\n )}) {(\n val coll27 = coll8.filter({(box27: Box) => ((((((blake2b256(box27.propositionBytes) == placeholder[Coll[Byte]](27)) && (box27.tokens.size > placeholder[Int](28))) && (box27.R4[Coll[Byte]].get == placeholder[Coll[Byte]](29))) && (box27.R5[Coll[Byte]].get == coll7)) && box27.R6[Boolean].get) && box27.R8[Boolean].get) && coll16.exists({(coll29: Coll[Byte]) => coll29 == box27.tokens(placeholder[Int](30))._1 }) })\n val coll28 = coll27.map({(box28: Box) => box28.tokens(placeholder[Int](31))._1 })\n ((((((((((((((((((func15(box22) >= func15(SELF)) && (box22.tokens.filter({(tuple29: (Coll[Byte], Long)) => tuple29._1 == coll7 }).size == placeholder[Int](32))) && (box22.R4[Int].get == placeholder[Int](33))) && (box22.R5[Coll[Byte]].get == coll9)) && (box22.R7[Coll[Coll[Byte]]].get == coll16)) && (box22.R8[Coll[Long]].get(placeholder[Int](34)) == l13)) && (box22.R8[Coll[Long]].get(placeholder[Int](35)) == coll3(placeholder[Int](36)))) && (box22.R8[Coll[Long]].get(placeholder[Int](37)) == l4)) && (box22.R8[Coll[Long]].get(placeholder[Int](38)) == l17)) && (box22.R8[Coll[Long]].get(placeholder[Int](39)) == l12)) && (box22.R8[Coll[Long]].get(placeholder[Int](40)) == coll3(placeholder[Int](41)))) && (box22.R8[Coll[Long]].get(placeholder[Int](42)) >= coll3(placeholder[Int](43)))) && (box22.R8[Coll[Long]].get(placeholder[Int](44)) == coll3(placeholder[Int](45)))) && (box22.R8[Coll[Long]].get(placeholder[Int](46)) >= l2 + placeholder[Long](47))) && (box22.R9[Coll[Coll[Byte]]].get(placeholder[Int](48)) == coll18)) && (box22.R9[Coll[Coll[Byte]]].get(placeholder[Int](49)) == coll11)) && (box22.R9[Coll[Coll[Byte]]].get(placeholder[Int](50)) == coll10(placeholder[Int](51)))) && (box22.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](52))) && coll28.indices.forall({(i29: Int) => !coll28.slice(i29 + placeholder[Int](53), coll27.size).exists({(coll31: Coll[Byte]) => coll31 == coll28(i29) }) })\n )} else { placeholder[Boolean](54) }\n )} else { placeholder[Boolean](55) }\n )} else { placeholder[Boolean](56) } || if ((l2 < l4) && (coll19.size == placeholder[Int](57))) {(\n val box21 = coll19(placeholder[Int](58))\n val l22 = func15(SELF) - l17 / placeholder[Long](59)\n (((((((((func15(box21) >= l22) && (box21.tokens(placeholder[Int](60))._1 == coll7)) && (box21.R4[Int].get == placeholder[Int](61))) && (box21.R5[Long].get >= l2 + placeholder[Long](62))) && (blake2b256(box21.R6[Coll[Byte]].get) == coll6)) && (box21.R7[Long].get == l22)) && (box21.R8[Long].get == l4)) && (box21.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](63))) && (box21.R9[Coll[Coll[Byte]]].get(placeholder[Int](64)) == coll18)) && (box21.R9[Coll[Coll[Byte]]].get(placeholder[Int](65)) == coll11)\n )} else { placeholder[Boolean](66) }) || if ((l2 < l14) && (coll20.size == placeholder[Int](67))) {(\n val box21 = coll20(placeholder[Int](68))\n (((((((box21.tokens(placeholder[Int](69))._1 == coll7) && (func15(box21) >= func15(SELF))) && (box21.R5[Coll[Byte]].get == blake2b256(coll9.append(SELF.id)))) && (box21.R4[Int].get == i1)) && (box21.R6[Coll[Byte]].get == coll6)) && (box21.R7[Coll[Coll[Byte]]].get == coll16)) && (box21.R8[Coll[Long]].get == coll3)) && (box21.R9[Coll[Coll[Byte]]].get == coll10)\n )} else { placeholder[Boolean](70) }))\n}",
"address": "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",
"assets": [
{
"tokenId": "6c174aeac07e284a20baa76ca8a5c30f41e9eac6c4ba0862d002e983d0389808",
"index": 0,
"amount": 1,
"name": "Dev Game [efd50f]",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 1,
"amount": 24000,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e209226dba607c3af40b68656e0536c72ded1a8c5e8872478ee15440f231f6990f4",
"sigmaType": "Coll[SByte]",
"renderedValue": "9226dba607c3af40b68656e0536c72ded1a8c5e8872478ee15440f231f6990f4"
},
"R6": {
"serializedValue": "0e20b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a",
"sigmaType": "Coll[SByte]",
"renderedValue": "b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a"
},
"R8": {
"serializedValue": "1108cebed10102eebed101d00f9003c0b802a0c21ea08d06",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1716135,1,1716151,1000,200,20000,250000,50000]"
},
"R7": {
"serializedValue": "1a0120758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9]"
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"additionalRegisters": {
"R5": {
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},
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}
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},
{
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"value": 1000000,
"index": 2,
"outputBlockId": "a3aa94cf6205597d8b769145b75e9d5e5aa210dbfe6fbca576845b2612a77a0d",
"outputTransactionId": "19c14c1016b97ed617a40f3654a0b60d075752beaa7101e266950367ad7fcb05",
"outputIndex": 0,
"ergoTree": "1906010100d17300",
"address": "FxyP1tYDuHYhZ28RZ",
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"additionalRegisters": {
"R4": {
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"renderedValue": "ad780c344a1e93e857063e2a42942cb23808bd43bf1ed37bb29147f45d57f51d"
}
}
}
],
"outputs": [
{
"boxId": "7aa55b09e24e3b1d47f933633f9ce59385336abbcb3457659e262cd964ded2b5",
"transactionId": "e560abdf918190d513bb82deffe547eba19b07021da6b6f8d6112963d16e19f3",
"blockId": "6aeb10a44217e71782be9b7a10b25a8442a969c3104831f639d7b42edd554481",
"value": 1099080,
"index": 0,
"globalIndex": 53424839,
"creationHeight": 1716153,
"settlementHeight": 1716154,
"ergoTree": "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",
"ergoTreeConstants": "0: 8\n1: Coll(45,-126,27,3,-30,-34,114,118,-69,-21,-77,-1,65,-20,55,79,-99,110,-38,67,100,97,-111,76,1,38,-126,-49,100,95,-92,-54)\n2: 0\n3: 2\n4: 0\n5: Coll(122,-94,-75,-37,-122,16,-18,-68,-23,35,110,21,-55,109,-47,84,-91,113,115,65,96,4,98,-91,-79,-37,114,2,-73,30,-45,38)\n6: 0\n7: 0\n8: 1\n9: 1\n10: 0\n11: 4\n12: -1\n13: false\n14: true\n15: 1\n16: 3\n17: 5\n18: 6\n19: 7\n20: 0\n21: 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)\n22: 0\n23: 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)\n24: Coll(-90,-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,-39)\n25: true\n26: 0\n27: 0\n28: 1\n29: 0\n30: 0\n31: 2\n32: 1\n33: 1\n34: 0\n35: 1\n36: 0\n37: 8\n38: 5\n39: 0\n40: 1\n41: 0\n42: 1\n43: 2\n44: 3\n45: 4\n46: 5\n47: 0\n48: 6\n49: 0\n50: 7\n51: false\n52: false\n53: false\n54: 1\n55: 1\n56: 1\n57: 1\n58: 0\n59: 5\n60: 1\n61: 10\n62: -1\n63: 1\n64: 0\n65: -1\n66: 1\n67: 1\n68: 0\n69: 0\n70: 1\n71: 0\n72: 1\n73: 2\n74: 3\n75: 4\n76: 5\n77: 6\n78: 7\n79: 8\n80: 0\n81: 0\n82: 1\n83: 2\n84: 2\n85: 3\n86: 3\n87: 5\n88: 5\n89: 4\n90: false\n91: false\n92: false\n93: false\n94: false\n95: true\n96: false\n97: 0\n98: Coll(-34,-95,53,-55,103,102,9,81,53,114,-127,-84,25,-103,-109,107,-112,126,-39,-83,-33,-115,43,-82,55,114,26,-29,53,126,107,-22)\n99: 1\n100: 0\n101: 0\n102: 1\n103: 0\n104: 1\n105: 2\n106: 3\n107: 4\n108: 5\n109: 6\n110: 7\n111: 8\n112: false\n113: 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 coll10 = CONTEXT.dataInputs\n val l11 = coll3(placeholder[Int](3))\n val l12 = coll3(placeholder[Int](4))\n val func13 = {(box13: Box) =>\n val coll15 = coll10.filter({(box15: Box) =>\n val opt17 = box15.R4[Coll[Byte]]\n (opt17.isDefined && (opt17.get == box13.R7[Coll[Byte]].get)) && (blake2b256(box15.propositionBytes) == placeholder[Coll[Byte]](5))\n })\n if (coll15.size > placeholder[Int](6)) {(\n val l16 = coll15.fold(coll15(placeholder[Int](7)), {(tuple16: (Box, Box)) =>\n val box18 = tuple16._2\n val box19 = tuple16._1\n if (box18.creationInfo._1 < box19.creationInfo._1) { box18 } else { box19 }\n }).creationInfo._1.toLong\n val l17 = l12 + placeholder[Long](8)\n if (l16 < l17) { l17 } else { l16 }\n )} else { l11 }\n }\n val coll14 = SELF.R9[Coll[Coll[Byte]]].get\n val coll15 = coll14(placeholder[Int](9))\n val func16 = {(box16: Box) =>\n box16.tokens.filter({(tuple18: (Coll[Byte], Long)) => tuple18._1 == coll15 }).fold(\n placeholder[Long](10), {(tuple18: (Long, (Coll[Byte], Long))) => tuple18._1 + tuple18._2._2 }\n )\n }\n val l17 = coll3(placeholder[Int](11))\n val coll18 = SELF.R5[Coll[Byte]].get\n val coll19 = tuple8._1\n val func20 = {(box20: Box) => box20.R9[Coll[Long]].get.fold((placeholder[Long](12), placeholder[Boolean](13)), {(tuple22: ((Long, Boolean), Long)) =>\n val tuple24 = tuple22._1\n val l25 = tuple22._2\n if (tuple24._2) { tuple24 } else { if (blake2b256(box20.R7[Coll[Byte]].get.append(coll18).append(longToByteArray(l25)).append(box20.R8[Coll[Byte]].get).append(box20.R4[Coll[Byte]].get).append(coll19)) == box20.R5[Coll[Byte]].get) { (l25, placeholder[Boolean](14)) } else { tuple24 } }\n }) }\n val l21 = coll3(placeholder[Int](15))\n val coll22 = SELF.R7[Coll[Coll[Byte]]].get\n val l23 = coll3(placeholder[Int](16))\n val l24 = coll3(placeholder[Int](17))\n val l25 = coll3(placeholder[Int](18))\n val l26 = coll3(placeholder[Int](19))\n val func27 = {(bool27: Boolean) => if (bool5 && (coll10.size > placeholder[Int](20))) {(\n val coll29 = coll10.filter({(box29: Box) => (((((blake2b256(box29.propositionBytes) == placeholder[Coll[Byte]](21)) && (box29.tokens.size > placeholder[Int](22))) && (box29.R4[Coll[Byte]].get == if (bool27) { placeholder[Coll[Byte]](23) } else { placeholder[Coll[Byte]](24) })) && (box29.R5[Coll[Byte]].get == coll9)) && if (bool27) { box29.R6[Boolean].get && (!box29.R8[Boolean].get) } else { placeholder[Boolean](25) }) && coll22.exists({(coll31: Coll[Byte]) => coll31 == box29.tokens(placeholder[Int](26))._1 }) })\n val coll30 = coll29.map({(box30: Box) => box30.tokens(placeholder[Int](27))._1 })\n val i31 = coll29.size\n val i32 = coll22.size\n val coll33 = OUTPUTS.filter({(box33: Box) => box33.propositionBytes == SELF.propositionBytes })\n if ((coll30.indices.forall({(i34: Int) => !coll30.slice(i34 + placeholder[Int](28), i31).exists({(coll36: Coll[Byte]) => coll36 == coll30(i34) }) }) && (i31 >= if (i32 == placeholder[Int](29)) { placeholder[Int](30) } else { i32 / placeholder[Int](31) + placeholder[Int](32) })) && (coll33.size == placeholder[Int](33))) {(\n val box34 = coll33(placeholder[Int](34))\n val coll35 = INPUTS.filter({(box35: Box) => (blake2b256(box35.propositionBytes) == coll6) && (box35.R5[Coll[Byte]].get == coll9) })\n if ((box34.R6[(Coll[Byte], Coll[Byte])].get._2 == Coll[Byte]()) && (coll35.size == placeholder[Int](35))) { ((func16(box34) >= func16(SELF) + func16(coll35(placeholder[Int](36)))) && (box34.R8[Coll[Long]].get(placeholder[Int](37)) >= l2 + placeholder[Long](38))) && ((((((((((((((box34.tokens(placeholder[Int](39))._1 == coll7) && (box34.R4[Int].get == i1)) && (i1 == placeholder[Int](40))) && (box34.R5[Coll[Byte]].get == coll18)) && (box34.R7[Coll[Coll[Byte]]].get == coll22)) && (box34.R8[Coll[Long]].get(placeholder[Int](41)) == l12)) && (box34.R8[Coll[Long]].get(placeholder[Int](42)) == l21)) && (box34.R8[Coll[Long]].get(placeholder[Int](43)) == l11)) && (box34.R8[Coll[Long]].get(placeholder[Int](44)) == l23)) && (box34.R8[Coll[Long]].get(placeholder[Int](45)) == l17)) && (box34.R8[Coll[Long]].get(placeholder[Int](46)) == l24 + if (bool27) { l25 } else { placeholder[Long](47) })) && (box34.R8[Coll[Long]].get(placeholder[Int](48)) == if (bool27) { placeholder[Long](49) } else { l25 })) && (box34.R8[Coll[Long]].get(placeholder[Int](50)) == l26)) && (box34.R9[Coll[Coll[Byte]]].get == coll14)) } else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n )} else { placeholder[Boolean](53) } }\n sigmaProp(i1 == placeholder[Int](54)) && sigmaProp(if ((bool5 && (INPUTS.size > placeholder[Int](55))) && (OUTPUTS.size > placeholder[Int](56))) {(\n val coll28 = coll10.filter({(box28: Box) => ((blake2b256(box28.propositionBytes) == coll6) && (box28.R6[Coll[Byte]].get == coll7)) && (box28.R5[Coll[Byte]].get != coll9) })\n if (coll28.size == placeholder[Int](57)) {(\n val box29 = coll28(placeholder[Int](58))\n val l30 = func13(box29)\n if ((((((blake2b256(box29.propositionBytes) == coll6) && (box29.R6[Coll[Byte]].get == coll7)) && (box29.creationInfo._1.toLong < l11)) && (l30 < l11 - placeholder[Long](59) - placeholder[Long](60))) && (func16(box29) >= l17)) && (box29.R9[Coll[Long]].get.size.toLong <= placeholder[Long](61))) {(\n val l31 = func20(box29)._1\n val bool32 = l31 != placeholder[Long](62)\n if (bool32) {(\n val coll33 = Coll[Byte]()\n val coll34 = if (coll9 == coll33) { box29.R5[Coll[Byte]].get } else {(\n val coll34 = coll10.filter({(box34: Box) => ((blake2b256(box34.propositionBytes) == coll6) && (box34.R5[Coll[Byte]].get == coll9)) && (box34.R6[Coll[Byte]].get == coll7) })\n if (coll34.size == placeholder[Int](63)) {(\n val box35 = coll34(placeholder[Int](64))\n val tuple36 = func20(box35)\n val l37 = tuple36._1\n if (tuple36._2 && (l37 != placeholder[Long](65))) {(\n val l38 = l31 * placeholder[Long](66) + l21 * l11 - l30\n val l39 = func13(box35)\n val l40 = l37 * placeholder[Long](67) + l21 * l11 - l39\n if ((l38 > l40) || ((l38 == l40) && (l30 < l39))) { box29.R5[Coll[Byte]].get } else { coll33 }\n )} else { coll33 }\n )} else { coll33 }\n )}\n if ((coll34 != coll33) && (coll34 != coll9)) {(\n val box35 = OUTPUTS(placeholder[Int](68))\n ((((((((((((((((((((((func16(box35) >= func16(SELF)) && (box35.tokens(placeholder[Int](69))._1 == coll7)) && (box35.R4[Int].get == i1)) && (i1 == placeholder[Int](70))) && (box35.R5[Coll[Byte]].get == coll18)) && (box35.R6[(Coll[Byte], Coll[Byte])].get._1 == coll19)) && (box35.R6[(Coll[Byte], Coll[Byte])].get._2 == coll34)) && (box35.R7[Coll[Coll[Byte]]].get == coll22)) && (box35.R8[Coll[Long]].get(placeholder[Int](71)) == l12)) && (box35.R8[Coll[Long]].get(placeholder[Int](72)) == l21)) && (box35.R8[Coll[Long]].get(placeholder[Int](73)) == l11)) && (box35.R8[Coll[Long]].get(placeholder[Int](74)) == l23)) && (box35.R8[Coll[Long]].get(placeholder[Int](75)) == l17)) && (box35.R8[Coll[Long]].get(placeholder[Int](76)) == l24)) && (box35.R8[Coll[Long]].get(placeholder[Int](77)) == l25)) && (box35.R8[Coll[Long]].get(placeholder[Int](78)) == l26)) && (box35.R8[Coll[Long]].get(placeholder[Int](79)) == l4)) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](80)) == coll14(placeholder[Int](81)))) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](82)) == coll15)) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](83)) == coll14(placeholder[Int](84)))) && ((box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](85)) == coll14(placeholder[Int](86))) || (l4 - placeholder[Long](87) + placeholder[Long](88) < l2))) && (box35.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](89))) && bool32\n )} else { placeholder[Boolean](90) }\n )} else { placeholder[Boolean](91) }\n )} else { placeholder[Boolean](92) }\n )} else { placeholder[Boolean](93) }\n )} else { placeholder[Boolean](94) }) || sigmaProp(func27(placeholder[Boolean](95))) || sigmaProp(func27(placeholder[Boolean](96))) || if ((l2 >= l4) && (\n OUTPUTS.size > placeholder[Int](97)\n )) {(\n val coll28 = OUTPUTS.filter({(box28: Box) => blake2b256(box28.propositionBytes) == placeholder[Coll[Byte]](98) })\n if (coll28.size == placeholder[Int](99)) {(\n val box29 = coll28(placeholder[Int](100))\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((box29.tokens(placeholder[Int](101))._1 == coll7) && (box29.R4[Int].get == i1)) && (i1 == placeholder[Int](102))) && (\n box29.R5[Coll[Byte]].get == coll18\n )\n ) && (box29.R6[(Coll[Byte], Coll[Byte])].get._1 == coll19)\n ) && (box29.R6[(Coll[Byte], Coll[Byte])].get._2 == coll9)\n ) && (box29.R7[Coll[Coll[Byte]]].get == coll22)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](103)) == l12)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](104)) == l21)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](105)) == l11)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](106)) == l23)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](107)) == l17)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](108)) == l24)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](109)) == l25)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](110)) == l26)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](111)) == l4)\n ) && (box29.R9[Coll[Coll[Byte]]].get == coll14)\n ) && (func16(box29) >= func16(SELF))\n )\n )} else { sigmaProp(placeholder[Boolean](112)) }\n )} else { sigmaProp(placeholder[Boolean](113)) }\n}",
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{
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{
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],
"additionalRegisters": {
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"renderedValue": "[1716135,1,1716151,1000,200,20000,250000,50000,1716168]"
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}
},
"spentTransactionId": "8be157ca4d68424ff9598eeeb4678c30abaa7b628e13d3dd76e300678820e5da",
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{
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