Transaction
ID: c7784d3a9b...11c8
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
67.98 ERG
Tokens:
Loading assets...
Outputs (14)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Unspent
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
67.99 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 815,668
Total coins transferred: 68 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000201 ERG
Raw Transaction Data
{
"id": "c7784d3a9b9c29d553f2bedd6a8d83409bdb7417e3c352b6860282f81efb11c8",
"blockId": "997b4fe9c0559625528055297abb8d41eb8b41a6a568b95d550df71594eb5734",
"inclusionHeight": 950362,
"timestamp": 1677615677067,
"index": 15,
"globalIndex": 4832105,
"numConfirmations": 815668,
"inputs": [
{
"boxId": "0d75e02f630b0b8c266dc6c4055eac27aab167d5cdead9d8cd14a933e400c462",
"value": 11000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "fc49d813d42af5ed0b58fa00c8016934ce3916db629bd6ecc2031e26e80aa090",
"outputTransactionId": "2e4c36419ca5b155f047c31f8a1abfd875377f4597063f8e549d4ea478b649d6",
"outputIndex": 0,
"outputGlobalIndex": 26906457,
"outputCreatedAt": 948078,
"outputSettledAt": 948080,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-73,-16,-100,27,10,-105,77,102,-103,-87,89,58,40,104,8,-83,18,116,-113,-88,2,90,-71,-83,-53,36,55,94,3,-107,-8,21)\n3: 1\n4: 0\n5: Coll(55,8,14,-89,-110,92,64,121,101,-14,112,19,-2,102,-46,-25,-42,-110,-26,-115,-64,-34,-110,25,-17,-2,72,25,-50,-88,-57,-77)\n6: 7200\n7: Coll(106,26,12,-10,30,-60,20,-119,22,40,30,109,-126,-95,-47,122,96,-18,-41,-124,82,0,64,29,82,49,55,127,70,67,-70,103)",
"ergoTreeScript": "{\n val coll1 = SELF.R4[Coll[Coll[Byte]]].get\n val i2 = coll1.size\n val coll3 = OUTPUTS.slice(placeholder[Int](0), i2)\n val coll4 = OUTPUTS(placeholder[Int](1)).propositionBytes\n val coll5 = blake2b256(coll4)\n sigmaProp(allOf(Coll[Boolean](i2 == coll3.size, coll1.zip(coll3).forall({(tuple6: (Coll[Byte], Box)) =>\n val box8 = tuple6._2\n (Coll[Coll[Byte]](tuple6._1) == box8.R4[Coll[Coll[Byte]]].get) && (box8.propositionBytes == coll4)\n }), if (coll5 == placeholder[Coll[Byte]](2)) { allOf(Coll[Boolean](INPUTS(placeholder[Int](3)).tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), HEIGHT - placeholder[Int](6) >= SELF.creationInfo._1)) } else { allOf(Coll[Boolean](INPUTS.exists({(box6: Box) => blake2b256(box6.propositionBytes) == placeholder[Coll[Byte]](7) }), coll5 == SELF.R6[Coll[Byte]].get)) })))\n}",
"address": "21oSXpSmAC6qp2H72o1YW4D9Dxq3mSkee28gWAFqqd9NRTx15VHM6RwVxScoDnN4jiTegJvto6yK4rZDV788EKrJdoftYXVdQDaeakfgJJhLSfpJcadGZLLwJQkpoRJpesAgY8QfkuyLTkVNbNNshvsA4x3kfvPFDGDQfn8AdN6hJ1FnibRdcj3uY9NQTjjLWNGb1XNdUQyGv73qBJobfaRm9GyXzk9wUq54VhKdcxzTjzuJTtCCv2cxBXKup4EzEEXDNWLcfsD8bNknob5bmUDuTGszsPZHcwAwXgcqsxKvcki7KUs7d666iyu5fNgvFTx8B3D1ageWpAD5RcBbmfiGNEL9k7BnwWiP2pU5DwhJzWH3iU",
"assets": [
{
"tokenId": "383d70ab083cc23336a46370fe730b2c51db0e831586b6d545202cbc33938ee1",
"index": 0,
"amount": 10,
"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[846f72637b75f4817eb3f6e8542cb2d92875cf1ddce0fd5b734fc7c9bb48ac60,c1f5aa4b1a713396a63f556df49c70add93b3471cbca893c6146fce5a4b95e76,730488119f223822c77c9c89fa73e1794116dd1503fcabf3fc9217ffe7b7b508,d4e03eda58a338f8f65b40de258407dbdbbd9b8ccca374f66be8d97e52c8a752,ed6b8b63d187198f3ba55468231b5c83c050f7273364211fcf3b1ca7526ff302,da06f26f55cca0ad06880e0e8fe40d4011373e526f6aafe47caba8f5fa169707,e09921d0a87bb63e94aa6074c090a903a280ebd8cfba862396e56668f7138fe1,d206d6f37bc63fae26fbb591d5d4b60181db35fb712ae6dfa2c5faf0078d66eb,e39047fa7025f5eb94f0b1a9d6d4728b5a4270ea1155e4e5b0e265db46589d5c,101f5f0995d90c80a9491815571ed1c9fc5522922fa3bbccbd575d1aa7255f90]"
},
"R5": {
"serializedValue": "1a0c4034363766623461663132623833396531353733333230633939633465616362396239396564643930623265613461326634326461303932643562643833636665046572676f0763617264616e6f3339685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b4767616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d360800000000000011480800000000000007d00800000000000000c840353137633931623465613638303136366464643366363762323762303237346332306262643261656238326236306561663562663534373162333766363834612c6173736574317677756e30613532786a763574633278393277677236783370367133753466726e6d7138713040653331356266636539616466623638363838646164313635613066323835626134373766613562373539356664346637663538303063303938636266636562390800000000000e7757",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[34363766623461663132623833396531353733333230633939633465616362396239396564643930623265613461326634326461303932643562643833636665,6572676f,63617264616e6f,39685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b47,616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d36,0000000000001148,00000000000007d0,00000000000000c8,35313763393162346561363830313636646464336636376232376230323734633230626264326165623832623630656166356266353437316233376636383461,6173736574317677756e30613532786a763574633278393277677236783370367133753466726e6d71387130,65333135626663653961646662363836383864616431363561306632383562613437376661356237353935666434663766353830306330393863626663656239,00000000000e7757]"
},
"R6": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
}
}
},
{
"boxId": "3bde9cd14b5f4a3bf1bc01a007cf0bebc06a1f9fa75b7ede44dbb125af7ed98c",
"value": 67984828076,
"index": 1,
"spendingProof": "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",
"outputBlockId": "357eba39037e477b5e6f2b63acd178d6d18df24af555b3f98eff5f8fd8b41fd6",
"outputTransactionId": "154dbc92d0f0b7119307f9ebdbd97f330afbf1ad48e155653c28b6a68721a66b",
"outputIndex": 12,
"outputGlobalIndex": 27009404,
"outputCreatedAt": 950345,
"outputSettledAt": 950349,
"ergoTree": "100304000e20a96b8049f0741c7255b60cf01954439d2e4b2d19ae7d8ebc688ecb190a33b5380400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-87,107,-128,73,-16,116,28,114,85,-74,12,-16,25,84,67,-99,46,75,45,25,-82,125,-114,-68,104,-114,-53,25,10,51,-75,56)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LG4ydEj62n9aymRyPCEbkBdzaubgvCWDH2oxHxFBfAUy9GhWDvteDbbUh5qhXxnW8R46qmEiZfkej8gt4kZYvbeobZJADMrWXwFJTsZ17euEcoAp3KDk31Q26okFpgK9SKdi4",
"assets": [
{
"tokenId": "517c91b4ea680166ddd3f67b27b0274c20bbd2aeb82b60eaf5bf5471b37f684a",
"index": 0,
"amount": 8802,
"name": "Rosen Test Wrap Token",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fc6c2070eb004fc08fcde1514dee56b1d0587477748d8af647179b098f52f559",
"index": 1,
"amount": 1041089681,
"name": "RsADA",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 2,
"amount": 741470,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "350bff7491aa9bf828a922fd8f50df0191c6ae586cb077d84b9caef5dd96cfbc",
"value": 1100000,
"index": 0,
"outputBlockId": "a7aeaa064590253e9f07e63a64d86b5d08c9508f9da13ccac29723e98eb7a0d6",
"outputTransactionId": "e3f3794c3bfe63a88a2703a2588bce143bdc40fbd06bbdb469bbfaf00cf4eb35",
"outputIndex": 0,
"ergoTree": "100504000400040004000402d802d601c2a7d602b2a5730000ea02d196830301937201c2b2a473010093c272027201938cb2db63087202730200018cb2db6308a77303000198b2e4c6a70510730400ade4c6a7041ad901030ecdee7203",
"address": "MZ4DGXjbMTDYv4wnEPCSzRGp3infV4oBqQvJhnnePTb61wYrGaS2oiNAbesgJphKS3v5tA3cqaEXUdgRP5EsKBihXwSSogs4RNVhhsYyQiYHoWNo3jB7Fm2DDQSVLJZCf41sd",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[02db3849f655693c28e3c44ededd546c6c3267b6f90c0f9ad9785061c387ca2e69,0249e1b4b331b93481cc812c024f1f8a198fe078895ad7f03ab890bd4e81fb5907,020e106e606e70e426a19900f42f3210420f53498c9956106d30b1837596dbc451,02ddd718f3080a04c2e9f2016dc13153f65d64da83ccfea433139c89236476e2b7,02e2c106d43c57936310f06d4fea9f6940dbf1c4e32cb99bdd7ac7b7714e545271,032bb38046b67ed49aa6f4d255bbe1c098ff2f7b682f9922a2a376862de266b16e,03c3374d06b092583835a3a93c7acbc6c449656881abff5d6b17df456a7f3d618b,02956d0fd87b81ebe8ea4763a64e126a548adef2eec3a9719683944100cb992bc5,02b980e0cbb817f80163485aea9ce59c3d6249d510733002a9fc6843718a540b07,03d7e6475ef5ceb9b0e9b0cad722c9cbfa3a13e8e94188ac963e11e4e66e9eaa2c]"
},
"R5": {
"serializedValue": "10020e10",
"sigmaType": "Coll[SInt]",
"renderedValue": "[7,8]"
}
}
}
],
"outputs": [
{
"boxId": "0783e685fda9a27b62d342a96d634a488dfe0df34348d967bfd0f73e6ac7c09c",
"transactionId": "c7784d3a9b9c29d553f2bedd6a8d83409bdb7417e3c352b6860282f81efb11c8",
"blockId": "997b4fe9c0559625528055297abb8d41eb8b41a6a568b95d550df71594eb5734",
"value": 300000,
"index": 0,
"globalIndex": 27009838,
"creationHeight": 950350,
"settlementHeight": 950362,
"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(38,8,54,88,-4,-30,-82,91,-104,72,-83,0,-73,-41,40,120,-54,-124,57,74,71,41,68,96,-47,28,67,-6,27,-82,115,-115)\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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"sigmaType": "Coll[Coll[SByte]]",
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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(38,8,54,88,-4,-30,-82,91,-104,72,-83,0,-73,-41,40,120,-54,-124,57,74,71,41,68,96,-47,28,67,-6,27,-82,115,-115)\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": [
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"name": "Ergo-RWT-V.beta",
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[c1f5aa4b1a713396a63f556df49c70add93b3471cbca893c6146fce5a4b95e76]"
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"mainChain": true
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{
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"index": 2,
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"creationHeight": 950350,
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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(38,8,54,88,-4,-30,-82,91,-104,72,-83,0,-73,-41,40,120,-54,-124,57,74,71,41,68,96,-47,28,67,-6,27,-82,115,-115)\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": [
{
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"index": 0,
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"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
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"index": 1,
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"serializedValue": "1a0120730488119f223822c77c9c89fa73e1794116dd1503fcabf3fc9217ffe7b7b508",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[730488119f223822c77c9c89fa73e1794116dd1503fcabf3fc9217ffe7b7b508]"
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{
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"creationHeight": 950350,
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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(38,8,54,88,-4,-30,-82,91,-104,72,-83,0,-73,-41,40,120,-54,-124,57,74,71,41,68,96,-47,28,67,-6,27,-82,115,-115)\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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"renderedValue": "[ed6b8b63d187198f3ba55468231b5c83c050f7273364211fcf3b1ca7526ff302]"
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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(38,8,54,88,-4,-30,-82,91,-104,72,-83,0,-73,-41,40,120,-54,-124,57,74,71,41,68,96,-47,28,67,-6,27,-82,115,-115)\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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"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(38,8,54,88,-4,-30,-82,91,-104,72,-83,0,-73,-41,40,120,-54,-124,57,74,71,41,68,96,-47,28,67,-6,27,-82,115,-115)\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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"renderedValue": "[e09921d0a87bb63e94aa6074c090a903a280ebd8cfba862396e56668f7138fe1]"
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"globalIndex": 27009845,
"creationHeight": 950350,
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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": 8,
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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": "{SigmaProp(ProveDlog(ECPoint(d0b75b,1b1e24,...)))}",
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"assets": [
{
"tokenId": "517c91b4ea680166ddd3f67b27b0274c20bbd2aeb82b60eaf5bf5471b37f684a",
"index": 0,
"amount": 200,
"name": "Rosen Test Wrap Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "47bfa69e17fa4eeb08a2cbeac7a8aceb9b5afa61f3c23668b5abfabc45c31975",
"transactionId": "c7784d3a9b9c29d553f2bedd6a8d83409bdb7417e3c352b6860282f81efb11c8",
"blockId": "997b4fe9c0559625528055297abb8d41eb8b41a6a568b95d550df71594eb5734",
"value": 67991128076,
"index": 12,
"globalIndex": 27009850,
"creationHeight": 950350,
"settlementHeight": 950362,
"ergoTree": "100304000e20a96b8049f0741c7255b60cf01954439d2e4b2d19ae7d8ebc688ecb190a33b5380400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-87,107,-128,73,-16,116,28,114,85,-74,12,-16,25,84,67,-99,46,75,45,25,-82,125,-114,-68,104,-114,-53,25,10,51,-75,56)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LG4ydEj62n9aymRyPCEbkBdzaubgvCWDH2oxHxFBfAUy9GhWDvteDbbUh5qhXxnW8R46qmEiZfkej8gt4kZYvbeobZJADMrWXwFJTsZ17euEcoAp3KDk31Q26okFpgK9SKdi4",
"assets": [
{
"tokenId": "517c91b4ea680166ddd3f67b27b0274c20bbd2aeb82b60eaf5bf5471b37f684a",
"index": 0,
"amount": 6602,
"name": "Rosen Test Wrap Token",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fc6c2070eb004fc08fcde1514dee56b1d0587477748d8af647179b098f52f559",
"index": 1,
"amount": 1041089681,
"name": "RsADA",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 2,
"amount": 739470,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d17162d0dd90e7d218d5f332375367013d0c723e4a7a80533db3f98ed760b3f0",
"mainChain": true
},
{
"boxId": "02a22d57a3c5bfb46c60589d5d9ccd494f658428069041fdf10369722e0d553e",
"transactionId": "c7784d3a9b9c29d553f2bedd6a8d83409bdb7417e3c352b6860282f81efb11c8",
"blockId": "997b4fe9c0559625528055297abb8d41eb8b41a6a568b95d550df71594eb5734",
"value": 1100000,
"index": 13,
"globalIndex": 27009851,
"creationHeight": 950350,
"settlementHeight": 950362,
"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": "40c8d5790f29ad348caf0a974ef7259650e9a43de981a2aec804698339641245",
"mainChain": true
}
],
"size": 5477,
"isUnconfirmed": false
}