Transaction
ID: 7bc6f74a81...bc23
Inputs (27)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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Value:
2.25 ERG
Tokens:
Loading assets...
Spent
Address:
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Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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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:
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Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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Settlement height:
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0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
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Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
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0.0003 ERG
Tokens:
Loading assets...
Spent
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Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
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Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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0.0003 ERG
Tokens:
Loading assets...
Spent
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Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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0.0003 ERG
Tokens:
Loading assets...
Spent
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0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
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0.0003 ERG
Tokens:
Loading assets...
Spent
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0.0003 ERG
Tokens:
Loading assets...
Spent
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0.0003 ERG
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0.0003 ERG
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0.0011 ERG
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Spent
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0.0003 ERG
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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:
2.25 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: 819,172
Total coins transferred: 2.26 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000441 ERG
Raw Transaction Data
{
"id": "7bc6f74a81e9de9b8e3d741310e3da78e8c77649a37bc83737630c65a9bcbc23",
"blockId": "907848bf038187c3e29a0439baad7a56996c0f44101458e3748776afa7c43c91",
"inclusionHeight": 950636,
"timestamp": 1677648248809,
"index": 11,
"globalIndex": 4833737,
"numConfirmations": 819172,
"inputs": [
{
"boxId": "5d67df33d2541ea6a9edc218e9e2a9774dd7e074729ec85887d599d44ed7a00b",
"value": 300000,
"index": 0,
"spendingProof": null,
"outputBlockId": "5242f338a1b93685ead2a23316bb74eec7c6167b4e268e523ec4ca047b907c90",
"outputTransactionId": "495eed1bcf96281c9087d8972dc9d24fcd76ea4d16f16bd68b6462494afe74b8",
"outputIndex": 5,
"outputGlobalIndex": 26940377,
"outputCreatedAt": 948780,
"outputSettledAt": 948785,
"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": 100,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b]"
}
}
},
{
"boxId": "56e6830097898dd3b7e558013af77cea6a8909e77e95dd45de8ce2eb2da160d8",
"value": 2247800000,
"index": 1,
"spendingProof": "f1d221db0b30c084ab9d407719ced27d036feb28a0ee6ba6076e34e774b6aabdea70fb198b63a96dc085a4b2c3a21794326e596c42b5479e",
"outputBlockId": "f68c781f8ebba79dc6c9a2d5013fbbd1478ce2d9a3528e562c8d97d77dc038be",
"outputTransactionId": "3045311cf068c766849ad481be6f73bf8ae2b9a0e6aade0c91a35a82cfd192d9",
"outputIndex": 1,
"outputGlobalIndex": 26930544,
"outputCreatedAt": 948582,
"outputSettledAt": 948586,
"ergoTree": "0008cd029024692c500c87e5e0a96ad1fbcb2ed340276f1b3cabd7ba43627585fab9f26c",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(902469,5f37a8,...)))}",
"address": "9fcYSB1WDwDYS1qfmtapAXAy4vMdvv6EtNM9G9ZKUY3xgYEZfxA",
"assets": [
{
"tokenId": "eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {}
},
{
"boxId": "2a95201d919929302bbd16afe49097d289774969aaa597e15f3b8105bf346d65",
"value": 300000,
"index": 2,
"spendingProof": null,
"outputBlockId": "60d914f8539dfc8cf918aa3aab608241ad779bee943399784d48b5a9317c9dc3",
"outputTransactionId": "40f3e31a443b7edd32689ff32c2137cf5bbca7379c958cb1d229e315d9fca380",
"outputIndex": 5,
"outputGlobalIndex": 26940227,
"outputCreatedAt": 948778,
"outputSettledAt": 948782,
"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": 100,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b]"
}
}
},
{
"boxId": "8e23c1e40671f338cb121185a438b5f1262de75bac5af668abb80f5cae184126",
"value": 300000,
"index": 3,
"spendingProof": null,
"outputBlockId": "0871d213b5c6d08d15b4d93186c953750f5cca635c1209a86f7d1e8c2a5115e0",
"outputTransactionId": "fa42da4c21aad19d81d0855048f64601b111f6aa76d1bb86e39839473db84e2d",
"outputIndex": 5,
"outputGlobalIndex": 26939728,
"outputCreatedAt": 948770,
"outputSettledAt": 948773,
"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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}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b]"
}
}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "ea3e70a3916f0b4738799aa2483911a9dc76300ab1df43091256ae309ed5f561",
"transactionId": "7bc6f74a81e9de9b8e3d741310e3da78e8c77649a37bc83737630c65a9bcbc23",
"blockId": "907848bf038187c3e29a0439baad7a56996c0f44101458e3748776afa7c43c91",
"value": 1100000,
"index": 0,
"globalIndex": 27018538,
"creationHeight": 950633,
"settlementHeight": 950636,
"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": 959,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b]"
},
"R5": {
"serializedValue": "0e0100",
"sigmaType": "Coll[SByte]",
"renderedValue": "00"
}
},
"spentTransactionId": "b4ce8208780af7574ac8de74d563222ea6845f45b9bb23ce3a82e2c86a164ed5",
"mainChain": true
},
{
"boxId": "7d3b3eddd003b7bda135e32ec49fedae084f639e73c3c9696e90efdcaafbb95c",
"transactionId": "7bc6f74a81e9de9b8e3d741310e3da78e8c77649a37bc83737630c65a9bcbc23",
"blockId": "907848bf038187c3e29a0439baad7a56996c0f44101458e3748776afa7c43c91",
"value": 1100000,
"index": 1,
"globalIndex": 27018539,
"creationHeight": 950633,
"settlementHeight": 950636,
"ergoTree": "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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": "1a0120eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b]"
},
"R5": {
"serializedValue": "1a0120315ee765dc4893c26c098e2ba9fda645a5817461113f96c2c767637cc6da1c96",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[315ee765dc4893c26c098e2ba9fda645a5817461113f96c2c767637cc6da1c96]"
},
"R6": {
"serializedValue": "0e208c3b5c505d67c8b68a0b4e5550ae4a7d170b1777efa52c597f3b17c40b7bba2d",
"sigmaType": "Coll[SByte]",
"renderedValue": "8c3b5c505d67c8b68a0b4e5550ae4a7d170b1777efa52c597f3b17c40b7bba2d"
},
"R7": {
"serializedValue": "0e20203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921",
"sigmaType": "Coll[SByte]",
"renderedValue": "203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921"
}
},
"spentTransactionId": "11e60af516dab54bda57574b9ee80159b9d0fff700fb6048db7941b7bf859b2e",
"mainChain": true
},
{
"boxId": "113a437d83724c8bd2fcd3a7aac3288b5ebb2fba5c3401468f93db9ec8c3d2f5",
"transactionId": "7bc6f74a81e9de9b8e3d741310e3da78e8c77649a37bc83737630c65a9bcbc23",
"blockId": "907848bf038187c3e29a0439baad7a56996c0f44101458e3748776afa7c43c91",
"value": 2252000000,
"index": 2,
"globalIndex": 27018540,
"creationHeight": 950633,
"settlementHeight": 950636,
"ergoTree": "0008cd029024692c500c87e5e0a96ad1fbcb2ed340276f1b3cabd7ba43627585fab9f26c",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(902469,5f37a8,...)))}",
"address": "9fcYSB1WDwDYS1qfmtapAXAy4vMdvv6EtNM9G9ZKUY3xgYEZfxA",
"assets": [
{
"tokenId": "eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {},
"spentTransactionId": "b4ce8208780af7574ac8de74d563222ea6845f45b9bb23ce3a82e2c86a164ed5",
"mainChain": true
},
{
"boxId": "913d89c8e74174fbb4912acadd8275428a772691db16f962dcc84a680a47a2cb",
"transactionId": "7bc6f74a81e9de9b8e3d741310e3da78e8c77649a37bc83737630c65a9bcbc23",
"blockId": "907848bf038187c3e29a0439baad7a56996c0f44101458e3748776afa7c43c91",
"value": 1100000,
"index": 3,
"globalIndex": 27018541,
"creationHeight": 950633,
"settlementHeight": 950636,
"ergoTree": "0008cd029024692c500c87e5e0a96ad1fbcb2ed340276f1b3cabd7ba43627585fab9f26c",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(902469,5f37a8,...)))}",
"address": "9fcYSB1WDwDYS1qfmtapAXAy4vMdvv6EtNM9G9ZKUY3xgYEZfxA",
"assets": [
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 0,
"amount": 2410,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b1c4959368ebadd8e6fb08c4b2636cb566cc6c319abbe41b3c3d8e75e147a79f",
"mainChain": true
},
{
"boxId": "992057bd74c53e33da1fe121d0b60dc7949f4505d50fd607036504f92f4820f1",
"transactionId": "7bc6f74a81e9de9b8e3d741310e3da78e8c77649a37bc83737630c65a9bcbc23",
"blockId": "907848bf038187c3e29a0439baad7a56996c0f44101458e3748776afa7c43c91",
"value": 1100000,
"index": 4,
"globalIndex": 27018542,
"creationHeight": 950633,
"settlementHeight": 950636,
"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": "c8c09fbf995178931735ccdc20a286d32fdc07e39c8f3566ba674c8b4fb80d5c",
"mainChain": true
}
],
"size": 2495,
"isUnconfirmed": false
}