Transaction
ID: 9faf3fe3fe...b4a1
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
1.26 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.44 ERG
Outputs (12)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.115 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.046 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.69 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.003 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.003 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.146 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.115 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.575 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.003 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.019 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Transaction Details
Confirmations: 1,085,423
Total coins transferred: 2.73 ERG
Fees: 0.019 ERG
Fees per byte: 0.000004045 ERG
Raw Transaction Data
{
"id": "9faf3fe3fed96ed362bddb48e2f3df67c43485ae3163702c1871c31b7850b4a1",
"blockId": "d2db1e6610027721e5440638168c254e6f38f18443990ea76e5684729c9b5169",
"inclusionHeight": 682940,
"timestamp": 1644487733955,
"index": 8,
"globalIndex": 2617633,
"numConfirmations": 1085423,
"inputs": [
{
"boxId": "a5e4a5b298aee8af558cf021a561aa7f149816779228624f0e7b4e12b318a55f",
"value": 10000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "18b5a587279b0658aacba71e4143c479a6014406fa4d9290363cef3ae2c75110",
"outputTransactionId": "b3457021c93cfc03f66424b6e3760a498469424ea6161b91aaf88a499e5c058b",
"outputIndex": 0,
"outputGlobalIndex": 13040535,
"outputCreatedAt": 682921,
"outputSettledAt": 682924,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 1\n4: false\n5: false\n6: 0\n7: -1\n8: false\n9: 1\n10: false\n11: 0\n12: 1\n13: 0\n14: 1\n15: 1\n16: 2\n17: 2\n18: 0\n19: 0\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: false\n26: false\n27: true",
"ergoTreeScript": "{\n val opt1 = SELF.R7[Coll[Long]]\n val opt2 = SELF.R8[Coll[(Coll[Byte], Coll[Byte])]]\n val bool3 = allOf(\n Coll[Boolean](\n SELF.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, SELF.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, SELF.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, opt1.isDefined, opt2.isDefined, INPUTS(placeholder[Int](0)) == SELF\n )\n )\n val box4 = INPUTS(placeholder[Int](1))\n val opt5 = box4.R5[Coll[(Coll[Byte], Coll[Byte])]]\n val opt6 = box4.R4[Coll[(Coll[Byte], Coll[Long])]]\n val box7 = OUTPUTS(placeholder[Int](2))\n val opt8 = box7.R7[Coll[Long]]\n val coll9 = box7.tokens\n if (bool3) {\n sigmaProp(\n if (if (if (if (bool3) { opt2.get.exists({(tuple10: (Coll[Byte], Coll[Byte])) => tuple10._1 == INPUTS(placeholder[Int](3)).propositionBytes }) } else {\n placeholder[Boolean](4)\n }) {\n allOf(\n Coll[Boolean](\n box4.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, box4.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, box4.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, box4.R7[Coll[Long]].isDefined, box4.R8[Coll[(Coll[Byte], Coll[Byte])]].isDefined\n )\n )\n } else { placeholder[Boolean](5) }) {\n opt5.get.forall(\n {(tuple10: (Coll[Byte], Coll[Byte])) =>\n opt6.get.map({(tuple12: (Coll[Byte], Coll[Long])) => tuple12._1 }).indexOf(tuple10._1, placeholder[Int](6)) != placeholder[Int](7)\n }\n )\n } else { placeholder[Boolean](8) } && if (if (box7.propositionBytes == SELF.propositionBytes) {\n allOf(\n Coll[Boolean](\n box7.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, box7.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, box7.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, box7.R7[Coll[Long]].isDefined, box7.R8[\n Coll[(Coll[Byte], Coll[Byte])]\n ].isDefined, box7.value == SELF.value, box7.tokens.size == placeholder[Int](9)\n )\n )\n } else { placeholder[Boolean](10) }) {(\n val coll10 = opt8.get\n val coll11 = opt1.get\n val l12 = coll11(placeholder[Int](11))\n val l13 = coll10(placeholder[Int](12))\n (\n ((coll10(placeholder[Int](13)) == l12 + placeholder[Long](14)) && ((l13 <= HEIGHT.toLong) && (l13 > coll11(placeholder[Int](15))))) && (\n coll10(placeholder[Int](16)) == coll11(placeholder[Int](17))\n )\n ) && if (l12 != placeholder[Long](18)) { SELF.tokens(placeholder[Int](19))._1 == coll9(placeholder[Int](20))._1 } else {(\n val coll14 = SELF.tokens\n if (coll14.size > placeholder[Int](21)) { coll14(placeholder[Int](22))._1 == coll9(placeholder[Int](23))._1 } else {\n coll9(placeholder[Int](24))._1 == SELF.id\n }\n )}\n )} else { placeholder[Boolean](25) }) {\n allOf(\n Coll[Boolean](\n box7.R4[Coll[(Coll[Byte], Coll[Long])]].get == opt6.get, box7.R5[Coll[(Coll[Byte], Coll[Byte])]].get == opt5.get, box7.R6[\n Coll[(Coll[Byte], Int)]\n ].get == box4.R6[Coll[(Coll[Byte], Int)]].get, opt8.get == box4.R7[Coll[Long]].get, box7.R8[Coll[(Coll[Byte], Coll[Byte])]].get == box4.R8[\n Coll[(Coll[Byte], Coll[Byte])]\n ].get\n )\n )\n } else { placeholder[Boolean](26) }\n )\n } else { sigmaProp(placeholder[Boolean](27)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c0",
"index": 0,
"amount": 1,
"name": "GetBlok.io SmartPool Display Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
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"sigmaType": "Coll[(Coll[SByte], Coll[SByte])]",
"renderedValue": "[[0008cd03a145c388ef2ac364fbb70add9cd6c74ef569c497ca0859a5c5da400a279f1d5a,396867714255517043506a506b4c4e7474537162473839386a41453779394d725255624b67796b3145696f6b70336f61717648],[0008cd037857911630ae9f1429a5b3803d5e4325e30b2fbadee507d6eca0c7cf1c9c898b,39684e6f66676677424d68683468413874476d39374e524d714254653974415444526b3663616b5842665941776d6f38704162],[0008cd0252c5b285a47cbb4bb18b09a65191b5c0a98ba6e21df8147475ded8c1740adfb2,3966395770616b564a516444646e44373458436e313563695375564b7a7150366a63747673584c685a747532473161454e796a],[0008cd034ce28c0d257932ffa127a5ff70cac2e1ccc9ba25ef80c496a8059f27d07d6c12,396833666361684e5273737067627270344b79596835445165634e4e6d61396e7276414c52463339705266344c784171374363],[0008cd033cd51db9f144bfc5f1f99cb132d9df4c7cb5b7dba04d8f1b7ad38e110ddcc2c7,39677662614c6447716f317451736159784a4d397a674259356164594d6b56545a793164374d53564b507658714a58735a5843],[0008cd03f21d9a7e974aa9c5d4fb6d72f00dbacfdb34b1a342b5fc3483a79aa5bfe81d0e,39694a534441484e564753366e5948757067614453524a767948755850634c6e4b624c51694a4a675333455569384270654448],[0008cd0264664239d4f0e88e1e580d9a70cb2d3051103263a9be7c054ca72f9b8f299439,39664848357152394e59686a5250715459664a6e6568666b785042574d393746626b4345625a635645727a73586e7442503962],[0008cd03372eedb90190dfcf9fbee35cfbc66dec0c4a1549bd992d3039a6306c03c08095,396774374775727671394563664b516345477769614d34767446516d796b4c58544251436257386d714b6553387642326f5863],[0008cd02f94670870c9c83d5360f404c2cc0e6ec86b4abd8f8f7e8621339ae4a022f6753,39675171757975654546726a453663316765536f57314c64666545316472526f65554741414775714b6944575063574147514c],[0008cd02a1b8567c25fc827682fcf05786b847967aad69b6b37dc6d0749458e06d94723b,39666b48534a7156517739546b7133516a48766a4364336e735a5368786138455135424e6962544663476e3859736579556951]]"
},
"R6": {
"serializedValue": "0c4c0e03240008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed37202706240008cd0287352ce40ff53154c5b3751a661908d3ca99edbb198e7ebb63d1d00e580f2efd06240008cd026dd353119c75189796b3fb01c60289399f5fa2e7e115f4d8e3ffcc0a4ba5326906",
"sigmaType": "Coll[(Coll[SByte], SInt)]",
"renderedValue": "[[0008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed372027,3],[0008cd0287352ce40ff53154c5b3751a661908d3ca99edbb198e7ebb63d1d00e580f2efd,3],[0008cd026dd353119c75189796b3fb01c60289399f5fa2e7e115f4d8e3ffcc0a4ba53269,3]]"
},
"R8": {
"serializedValue": "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",
"sigmaType": "Coll[(Coll[SByte], Coll[SByte])]",
"renderedValue": "[[100804000401040004000e204f5c05967a2a68d5fe0cdd7a688289f5b1a8aef7d24cab71c20ab8896068e0a80100010108cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7ea02d1afe4c6a7040c3c0e11d901013c0e11d801d603dc0c1aada5d9010363c27203028c7201017300959472037301d802d604b2a5720300d605db630872049591b172057302d801d606b27205730300ed938c7206017304938c720602c17204730573067307,566f746520546f6b656e204469737472696275746f72],[0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7,3967556962486f616569774b5a53707967685a4536594d455a564a753977734b7a465332335778525671366e7a547663476f55]]"
},
"R7": {
"serializedValue": "1104b002d2ae53aaf95008",
"sigmaType": "Coll[SLong]",
"renderedValue": "[152,682921,663125,4]"
},
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[(Coll[SByte], Coll[SLong])]",
"renderedValue": "[[0008cd03a145c388ef2ac364fbb70add9cd6c74ef569c497ca0859a5c5da400a279f1d5a,[8955,100000000,0,0]],[0008cd037857911630ae9f1429a5b3803d5e4325e30b2fbadee507d6eca0c7cf1c9c898b,[5560,100000000,72000000,0]],[0008cd0252c5b285a47cbb4bb18b09a65191b5c0a98ba6e21df8147475ded8c1740adfb2,[22389,5000000000,0,0]],[0008cd034ce28c0d257932ffa127a5ff70cac2e1ccc9ba25ef80c496a8059f27d07d6c12,[0,100000000,46000000,5]],[0008cd033cd51db9f144bfc5f1f99cb132d9df4c7cb5b7dba04d8f1b7ad38e110ddcc2c7,[25760,1000000000,334000000,0]],[0008cd03f21d9a7e974aa9c5d4fb6d72f00dbacfdb34b1a342b5fc3483a79aa5bfe81d0e,[3247,3000000000,119000000,0]],[0008cd0264664239d4f0e88e1e580d9a70cb2d3051103263a9be7c054ca72f9b8f299439,[1796,100000000,64000000,0]],[0008cd03372eedb90190dfcf9fbee35cfbc66dec0c4a1549bd992d3039a6306c03c08095,[10013,2000000000,387000000,0]],[0008cd02f94670870c9c83d5360f404c2cc0e6ec86b4abd8f8f7e8621339ae4a022f6753,[8340,100000000,0,0]],[0008cd02a1b8567c25fc827682fcf05786b847967aad69b6b37dc6d0749458e06d94723b,[11342,500000000,421000000,0]]]"
}
}
},
{
"boxId": "497c3cc6c8dddd9eb4a2cb785ce37ee99a50e083676aab091a5a728d2f83446d",
"value": 10000000,
"index": 1,
"spendingProof": "7fc547051c9b6d8432271d3bfd48d8f5c14ec00d6aa42841e7e97fc7a4c16e06f10980e03221bb605acb2b42095cb7567a58712dd3163cc6",
"outputBlockId": "d2db1e6610027721e5440638168c254e6f38f18443990ea76e5684729c9b5169",
"outputTransactionId": "3212c74235940a39f340aca0631d44514bb6af14348f094860fee23416b4f75f",
"outputIndex": 1,
"outputGlobalIndex": 13041943,
"outputCreatedAt": 682938,
"outputSettledAt": 682940,
"ergoTree": "100804000401040004000e204f5c05967a2a68d5fe0cdd7a688289f5b1a8aef7d24cab71c20ab8896068e0a80100010108cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7ea02d1afe4c6a7040c3c0e11d901013c0e11d801d603dc0c1aada5d9010363c27203028c7201017300959472037301d802d604b2a5720300d605db630872049591b172057302d801d606b27205730300ed938c7206017304938c720602c17204730573067307",
"ergoTreeConstants": "0: 0\n1: -1\n2: 0\n3: 0\n4: Coll(79,92,5,-106,122,42,104,-43,-2,12,-35,122,104,-126,-119,-11,-79,-88,-82,-9,-46,76,-85,113,-62,10,-72,-119,96,104,-32,-88)\n5: false\n6: true\n7: SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))",
"ergoTreeScript": "{sigmaProp(SELF.R4[Coll[(Coll[Byte], Coll[Long])]].get.forall({(tuple1: (Coll[Byte], Coll[Long])) =>\n val i3 = OUTPUTS.map({(box3: Box) => box3.propositionBytes }).indexOf(tuple1._1, placeholder[Int](0))\n if (i3 != placeholder[Int](1)) {(\n val box4 = OUTPUTS(i3)\n val coll5 = box4.tokens\n if (coll5.size > placeholder[Int](2)) {(\n val tuple6 = coll5(placeholder[Int](3))\n (tuple6._1 == placeholder[Coll[Byte]](4)) && (tuple6._2 == box4.value)\n )} else { placeholder[Boolean](5) }\n )} else { placeholder[Boolean](6) }\n })) && placeholder[SigmaProp](7)}",
"address": "5myzaZfXxd9b8H7695FKNa6UMYgM43KQCV9KPLC8QffhVSmbjMQcapFWUjcnTUpr2LhaqTN6sHU6JqQpaUtqB47q93brG1TY5166XvJDAotEV96EnH1P5whp7K2YHgx12TdRvhnc9aJjGEQAfBXG8fL9FHrx5VH4QoXmRbYt8V8LtQ37iMwDTVGHVKpLpU2JpQT25jQXAWcgdeVjKtJX7q3mUkEck3QXdQQHub688azmn4oLoq76auhr22gtV5J4VwL",
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{
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"index": 0,
"amount": 2706000000,
"name": "GetBlok.io Soft-Fork Governance Token",
"decimals": 9,
"type": "EIP-004"
}
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"sigmaType": "Coll[SLong]",
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{
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"value": 1263000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "d2db1e6610027721e5440638168c254e6f38f18443990ea76e5684729c9b5169",
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"ergoTree": "103604000e20c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c004020400010104020101010004020500040404020500040405d00f0580897a040404020500040404000580897a050004000580897a0400040204000404040104040401050001000401040105000100040105000400040101000101050001010400050004000400040001000ec204101c0400040204000402010001000400040101000402010004000402040005020402040404040500040004000400040004000400010001000101d809d601c6a70711d602c6a7080c3c0e0ed60396830601e6c6a7040c3c0e11e6c6a7050c3c0e0ee6c6a7060c4c0ee67201e6720293b2a4730000a7d604b2a4730100d605c67204050c3c0e0ed606c67204040c3c0e11d607b2a5730200d608c672070711d609db63087207957203d195ed9595957203aee47202d9010a3c0e0e938c720a01c2b2a4730300730496830501e6c67204040c3c0e11e6c67204050c3c0e0ee6c67204060c4c0ee6c672040711e6c67204080c3c0e0e7305afe47205d9010a3c0e0e94dc0c1aade47206d9010c3c0e118c720c01028c720a01730673077308959593c27207c2a796830701e6c67207040c3c0e11e6c67207050c3c0e0ee6c67207060c4c0ee6c672070711e6c67207080c3c0e0e93c17207c1a793b1db630872077309730ad804d60ae47208d60be47201d60cb2720b730b00d60db2720a730c00ededed93b2720a730d009a720c730eed90720d7ea30591720db2720b730f0093b2720a731000b2720b7311009594720c7312938cb2db6308a7731300018cb2720973140001d801d60edb6308a79591b1720e7315938cb2720e731600018cb2720973170001938cb2720973180001c5a773199683050193e4c67207040c3c0e11e4720693e4c67207050c3c0e0ee4720593e4c67207060c4c0ee4c67204060c4c0e93e47208e4c67204071193e4c67207080c3c0e0ee4c67204080c3c0e0e731ad1731b0101d805d601c2a7d602b5a4d901026393c272027201d603b17202d604b2a4730000d605730195ef95ed917203730293c5b27202730300c5a7730495937203730573067307d1dad9010601957206d807d608e4c6b2a4730800040c3c0e11d609e4c67204040c3c0e11d60a99b072027309d9010a41639a8c720a01c18c720a02b0b57209d9010a3c0e11d801d60c8c720a028fb2720c730a00b2720c730b00730cd9010a413c0e119a8c720a01b28c8c720a0202730d00d60bade4c67204060c4c0ed9010b4c0ed801d60d9d9c7e8c720b0205720a730e86028c720b0199720d9e720d730fd60cada5d9010c63c2720cd60dada5d9010d63c1720dd60eb0b57208d9010e3c0e11d801d6108c720e028fb27210731000b272107311007312d9010e413c0e119a8c720e01b28c8c720e0202731300edededaf7208d9010f3c0e11d807d6118c720f01d612dc0c1aad7209d901123c0e118c7212010272117314d6138c720f02d614dad9011405d801d6169d9c99b0720b720ad90116414d0e998c7216018c8c721602029c73157eb17208057214b072087316d90116413c0e119a8c721601b28c8c721602027317009972169e7216731801b27213731900d615b27213731a00d616dc0c1a720c027211731bd617b27213731c0095947212731dd801d6189ab2b2ad7209d901183c0e118c721802721200731e00721495927218721595947216731fed93b2720d721600721893721773207321ed93721673229372177218959272147215959472167323ed93b2720d721600721493721773247325ed93721673269372177214af720bd9010f4d0ed801d6118c720f02959172117327d801d612dc0c1a720c028c720f01732895947212732993c1b2a57212007211732a732b9591720e732caea5d9010f63ed93c1720f720e93c2720f7201732d9594b2e4c672040711732e00732f938cb2db63087204733000017205d801d60fdb630872049591b1720f7331938cb2720f73320001720593c57204720573330193c272047334d17335",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "b54ac86d7db11f005f810e6b9ce01bbca32a81ade231a72d89cb5044c0800d93",
"value": 1443000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "18b5a587279b0658aacba71e4143c479a6014406fa4d9290363cef3ae2c75110",
"outputTransactionId": "b3457021c93cfc03f66424b6e3760a498469424ea6161b91aaf88a499e5c058b",
"outputIndex": 5,
"outputGlobalIndex": 13040540,
"outputCreatedAt": 682921,
"outputSettledAt": 682924,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "d011c5c65dbe4361aa179419c621a92a4f61e2c998810fefcf8ecf3e5573e9a7",
"transactionId": "9faf3fe3fed96ed362bddb48e2f3df67c43485ae3163702c1871c31b7850b4a1",
"blockId": "d2db1e6610027721e5440638168c254e6f38f18443990ea76e5684729c9b5169",
"value": 10000000,
"index": 0,
"globalIndex": 13041998,
"creationHeight": 682938,
"settlementHeight": 682940,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 1\n4: false\n5: false\n6: 0\n7: -1\n8: false\n9: 1\n10: false\n11: 0\n12: 1\n13: 0\n14: 1\n15: 1\n16: 2\n17: 2\n18: 0\n19: 0\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: false\n26: false\n27: true",
"ergoTreeScript": "{\n val opt1 = SELF.R7[Coll[Long]]\n val opt2 = SELF.R8[Coll[(Coll[Byte], Coll[Byte])]]\n val bool3 = allOf(\n Coll[Boolean](\n SELF.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, SELF.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, SELF.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, opt1.isDefined, opt2.isDefined, INPUTS(placeholder[Int](0)) == SELF\n )\n )\n val box4 = INPUTS(placeholder[Int](1))\n val opt5 = box4.R5[Coll[(Coll[Byte], Coll[Byte])]]\n val opt6 = box4.R4[Coll[(Coll[Byte], Coll[Long])]]\n val box7 = OUTPUTS(placeholder[Int](2))\n val opt8 = box7.R7[Coll[Long]]\n val coll9 = box7.tokens\n if (bool3) {\n sigmaProp(\n if (if (if (if (bool3) { opt2.get.exists({(tuple10: (Coll[Byte], Coll[Byte])) => tuple10._1 == INPUTS(placeholder[Int](3)).propositionBytes }) } else {\n placeholder[Boolean](4)\n }) {\n allOf(\n Coll[Boolean](\n box4.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, box4.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, box4.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, box4.R7[Coll[Long]].isDefined, box4.R8[Coll[(Coll[Byte], Coll[Byte])]].isDefined\n )\n )\n } else { placeholder[Boolean](5) }) {\n opt5.get.forall(\n {(tuple10: (Coll[Byte], Coll[Byte])) =>\n opt6.get.map({(tuple12: (Coll[Byte], Coll[Long])) => tuple12._1 }).indexOf(tuple10._1, placeholder[Int](6)) != placeholder[Int](7)\n }\n )\n } else { placeholder[Boolean](8) } && if (if (box7.propositionBytes == SELF.propositionBytes) {\n allOf(\n Coll[Boolean](\n box7.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, box7.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, box7.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, box7.R7[Coll[Long]].isDefined, box7.R8[\n Coll[(Coll[Byte], Coll[Byte])]\n ].isDefined, box7.value == SELF.value, box7.tokens.size == placeholder[Int](9)\n )\n )\n } else { placeholder[Boolean](10) }) {(\n val coll10 = opt8.get\n val coll11 = opt1.get\n val l12 = coll11(placeholder[Int](11))\n val l13 = coll10(placeholder[Int](12))\n (\n ((coll10(placeholder[Int](13)) == l12 + placeholder[Long](14)) && ((l13 <= HEIGHT.toLong) && (l13 > coll11(placeholder[Int](15))))) && (\n coll10(placeholder[Int](16)) == coll11(placeholder[Int](17))\n )\n ) && if (l12 != placeholder[Long](18)) { SELF.tokens(placeholder[Int](19))._1 == coll9(placeholder[Int](20))._1 } else {(\n val coll14 = SELF.tokens\n if (coll14.size > placeholder[Int](21)) { coll14(placeholder[Int](22))._1 == coll9(placeholder[Int](23))._1 } else {\n coll9(placeholder[Int](24))._1 == SELF.id\n }\n )}\n )} else { placeholder[Boolean](25) }) {\n allOf(\n Coll[Boolean](\n box7.R4[Coll[(Coll[Byte], Coll[Long])]].get == opt6.get, box7.R5[Coll[(Coll[Byte], Coll[Byte])]].get == opt5.get, box7.R6[\n Coll[(Coll[Byte], Int)]\n ].get == box4.R6[Coll[(Coll[Byte], Int)]].get, opt8.get == box4.R7[Coll[Long]].get, box7.R8[Coll[(Coll[Byte], Coll[Byte])]].get == box4.R8[\n Coll[(Coll[Byte], Coll[Byte])]\n ].get\n )\n )\n } else { placeholder[Boolean](26) }\n )\n } else { sigmaProp(placeholder[Boolean](27)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c0",
"index": 0,
"amount": 1,
"name": "GetBlok.io SmartPool Display Token",
"decimals": 0,
"type": "EIP-004"
}
],
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"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
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"mainChain": true
},
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"ergoTree": "0008cd0287352ce40ff53154c5b3751a661908d3ca99edbb198e7ebb63d1d00e580f2efd",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(87352c,619230,...)))}",
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"ergoTree": "0008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed372027",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6d9d81,e53882,...)))}",
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(785791,bfe537,...)))}",
"address": "9hNofgfwBMhh4hA8tGm97NRMqBTe9tATDRk6cakXBfYAwmo8pAb",
"assets": [
{
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"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": "3a3c9b9d58b8d5b830c9ce1d769a2f13e9c7578240b2bd1714fdccc756a3f191",
"mainChain": true
},
{
"boxId": "6e4c6dba684f69613fdb1c70eaee4f84f59ee9697e900e6ee50d6311548e9d8b",
"transactionId": "9faf3fe3fed96ed362bddb48e2f3df67c43485ae3163702c1871c31b7850b4a1",
"blockId": "d2db1e6610027721e5440638168c254e6f38f18443990ea76e5684729c9b5169",
"value": 5000000,
"index": 11,
"globalIndex": 13042009,
"creationHeight": 682938,
"settlementHeight": 682940,
"ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
"address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "caa0d568bcfbd9bcbe723b7a16239442ef4713606057f790dcc2449961ec6373",
"mainChain": true
}
],
"size": 4697,
"isUnconfirmed": false
}