Transaction
ID: 75b1ccb3f4...7976
Inputs (25)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
2.3 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.3 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 809,875
Total coins transferred: 2.31 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000453 ERG
Raw Transaction Data
{
"id": "75b1ccb3f4f3cc73c66ea22ab575799734fb9a3bb9cb7974b17245eb358e7976",
"blockId": "49cc22a57927ef943d43c221294847a4d4ce57937f765ebbc52c209925e426d1",
"inclusionHeight": 948538,
"timestamp": 1677395991387,
"index": 7,
"globalIndex": 4819585,
"numConfirmations": 809875,
"inputs": [
{
"boxId": "c91b29502ed204bc2e099ec772d37744559d5919150d3df6a944e9254ed604dc",
"value": 300000,
"index": 0,
"spendingProof": null,
"outputBlockId": "8c2b98981e845ea52d96fca101aca0a5cb924368f15e9806faf5f1b88507ba78",
"outputTransactionId": "995beece5ccf998396e4e6710d89669001d005af0c6ba92dfe391ef3bef37e0b",
"outputIndex": 8,
"outputGlobalIndex": 26925143,
"outputCreatedAt": 948434,
"outputSettledAt": 948446,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(58,-56,-87,13,10,-88,-59,-59,14,-103,-35,37,-120,-87,-112,-3,55,-75,-45,-82,-25,14,50,-43,98,65,-12,30,-44,-98,-97,3)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(61,-29,117,6,-4,104,93,113,-86,-26,-56,-106,119,31,60,-127,-7,28,-78,124,-45,14,79,125,18,7,107,-78,-91,-70,106,56)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 1,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 1,
"amount": 90,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029]"
}
}
},
{
"boxId": "11605f8fd6d354c435a96800012e733f97355ee66e9ab1e331cd338af3c6c5e6",
"value": 2298900000,
"index": 1,
"spendingProof": "8e036570fc312416481f9d81b0d272bb4b9b1665ca2965685e7daa305b9922d9b74232cc0257a7b67d220a86648311d8e0acccfccd9fec1b",
"outputBlockId": "56e3adf4dd7035ea905482132d6673fb1ec8e05767f00ac17a597c42ba3407db",
"outputTransactionId": "155d8b03e2f0aaf855b3e487f0e647ba34f181f243fb51a51ec96e50eb097829",
"outputIndex": 2,
"outputGlobalIndex": 26904838,
"outputCreatedAt": 948046,
"outputSettledAt": 948050,
"ergoTree": "0008cd033ec49de7bde69a8bb0ed2cccd2fd66d544bfdf2194efb85188e6220961546503",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3ec49d,fdecef,...)))}",
"address": "9gwT1vCxXdHSvTaSVPxNMo4Cx3A2WpPgkHSzkFMfrRyyyuxum5m",
"assets": [
{
"tokenId": "484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {}
},
{
"boxId": "8f7c5805714110297f776a8091016297445466a052095a00d3b9e5c614c7a7b5",
"value": 300000,
"index": 2,
"spendingProof": null,
"outputBlockId": "cf35d08633f908d5337b0ff97b0ff3486afde63d3f43cb60486eca0855b73de8",
"outputTransactionId": "8f4100c41c00ee4bdc120a4bf7c932c15e3bdfc89bee6aca3cf71648d4a0caf2",
"outputIndex": 8,
"outputGlobalIndex": 26924686,
"outputCreatedAt": 948415,
"outputSettledAt": 948429,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(58,-56,-87,13,10,-88,-59,-59,14,-103,-35,37,-120,-87,-112,-3,55,-75,-45,-82,-25,14,50,-43,98,65,-12,30,-44,-98,-97,3)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(61,-29,117,6,-4,104,93,113,-86,-26,-56,-106,119,31,60,-127,-7,28,-78,124,-45,14,79,125,18,7,107,-78,-91,-70,106,56)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 1,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 1,
"amount": 90,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029]"
}
}
},
{
"boxId": "3bc6e94b559ed7ee77194d59b9f5cd938f2d7ceb2f60e0870ffc55319e8ff1bb",
"value": 300000,
"index": 3,
"spendingProof": null,
"outputBlockId": "976fa36c833df3bd283880dd4e5d453f942b3a1235ce5d6b68abeb2915b5bb6e",
"outputTransactionId": "6c5f487126e7b10711b65b32675fe35523000f5ac7f73862da2a1d05fa9da17e",
"outputIndex": 8,
"outputGlobalIndex": 26924421,
"outputCreatedAt": 948407,
"outputSettledAt": 948417,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(58,-56,-87,13,10,-88,-59,-59,14,-103,-35,37,-120,-87,-112,-3,55,-75,-45,-82,-25,14,50,-43,98,65,-12,30,-44,-98,-97,3)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(61,-29,117,6,-4,104,93,113,-86,-26,-56,-106,119,31,60,-127,-7,28,-78,124,-45,14,79,125,18,7,107,-78,-91,-70,106,56)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[Coll[SByte]]",
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"index": 24,
"spendingProof": null,
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"outputTransactionId": "155d8b03e2f0aaf855b3e487f0e647ba34f181f243fb51a51ec96e50eb097829",
"outputIndex": 0,
"outputGlobalIndex": 26904836,
"outputCreatedAt": 948046,
"outputSettledAt": 948050,
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(58,-56,-87,13,10,-88,-59,-59,14,-103,-35,37,-120,-87,-112,-3,55,-75,-45,-82,-25,14,50,-43,98,65,-12,30,-44,-98,-97,3)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(61,-29,117,6,-4,104,93,113,-86,-26,-56,-106,119,31,60,-127,-7,28,-78,124,-45,14,79,125,18,7,107,-78,-91,-70,106,56)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"assets": [
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029]"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "00"
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"dataInputs": [],
"outputs": [
{
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"transactionId": "75b1ccb3f4f3cc73c66ea22ab575799734fb9a3bb9cb7974b17245eb358e7976",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"assets": [
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"index": 0,
"amount": 965,
"name": "Cardano-RWT-V.beta",
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"renderedValue": "[484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029]"
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{
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"index": 1,
"globalIndex": 26928373,
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"ergoTreeConstants": "0: 0\n1: Coll(-6,-64,-122,-29,-103,68,59,81,-106,-10,108,82,-106,-18,-75,-119,-52,-118,58,-101,1,-121,-85,42,77,-29,-118,-71,-77,-30,-13,-67)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 1\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 1,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029]"
},
"R5": {
"serializedValue": "1a01201443049265a7c387824385cc5975f8208e675ee90065b1f0add27f07d7c0bcfe",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[1443049265a7c387824385cc5975f8208e675ee90065b1f0add27f07d7c0bcfe]"
},
"R6": {
"serializedValue": "0e2053f4df59d08ad60075ccb9a9172617e2954153ee3b6bff22a32d2d9b7859ed23",
"sigmaType": "Coll[SByte]",
"renderedValue": "53f4df59d08ad60075ccb9a9172617e2954153ee3b6bff22a32d2d9b7859ed23"
},
"R7": {
"serializedValue": "0e20203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921",
"sigmaType": "Coll[SByte]",
"renderedValue": "203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921"
}
},
"spentTransactionId": "0592ab4fe0d0cb21086ecd809abf7381b74280023e480d08ee6f6ebcfb02a75f",
"mainChain": true
},
{
"boxId": "9cee9a01ce26301fbec2e7b0e709e1fa1c394395b002acf0f936106b89671dc5",
"transactionId": "75b1ccb3f4f3cc73c66ea22ab575799734fb9a3bb9cb7974b17245eb358e7976",
"blockId": "49cc22a57927ef943d43c221294847a4d4ce57937f765ebbc52c209925e426d1",
"value": 2302500000,
"index": 2,
"globalIndex": 26928374,
"creationHeight": 948529,
"settlementHeight": 948538,
"ergoTree": "0008cd033ec49de7bde69a8bb0ed2cccd2fd66d544bfdf2194efb85188e6220961546503",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3ec49d,fdecef,...)))}",
"address": "9gwT1vCxXdHSvTaSVPxNMo4Cx3A2WpPgkHSzkFMfrRyyyuxum5m",
"assets": [
{
"tokenId": "484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {},
"spentTransactionId": "ed8396a6f475ac10dc7fb7b27b2211410f7b60b0e06af092ff243da972a0501c",
"mainChain": true
},
{
"boxId": "286b89b73be1618c7ec851394331258d1a2f661feae36f06d78bad48316dea08",
"transactionId": "75b1ccb3f4f3cc73c66ea22ab575799734fb9a3bb9cb7974b17245eb358e7976",
"blockId": "49cc22a57927ef943d43c221294847a4d4ce57937f765ebbc52c209925e426d1",
"value": 1100000,
"index": 3,
"globalIndex": 26928375,
"creationHeight": 948529,
"settlementHeight": 948538,
"ergoTree": "0008cd033ec49de7bde69a8bb0ed2cccd2fd66d544bfdf2194efb85188e6220961546503",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3ec49d,fdecef,...)))}",
"address": "9gwT1vCxXdHSvTaSVPxNMo4Cx3A2WpPgkHSzkFMfrRyyyuxum5m",
"assets": [
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 0,
"amount": 2070,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "af1f60044812afe7a788524bb4c809e02cbe4aa3eb882bf1a9e41f8e8d177573",
"mainChain": true
},
{
"boxId": "633a222df1a0e93994a550e2abb80e53a02a23131767545d787517a7cfa3899d",
"transactionId": "75b1ccb3f4f3cc73c66ea22ab575799734fb9a3bb9cb7974b17245eb358e7976",
"blockId": "49cc22a57927ef943d43c221294847a4d4ce57937f765ebbc52c209925e426d1",
"value": 1100000,
"index": 4,
"globalIndex": 26928376,
"creationHeight": 948529,
"settlementHeight": 948538,
"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)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "6dc840cc15465e9054e181d6117b1ab6a1d57bc8e6e246d9eadd229f733ef408",
"mainChain": true
}
],
"size": 2427,
"isUnconfirmed": false
}