Transaction
ID: aefb9ce137...a4ce
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.053 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.123 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.053 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.12 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 18,338
Total coins transferred: 0.177 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000631 ERG
Raw Transaction Data
{
"id": "aefb9ce137e864c8bfc441b5a2c922dc9eb446b8aadfe2995d47928755cea4ce",
"blockId": "d7b26db8a0a8f0722a40ac379267a88d2055813ff1a1d7b3f2d00caf33002d2b",
"inclusionHeight": 1743211,
"timestamp": 1773666564072,
"index": 5,
"globalIndex": 10454114,
"numConfirmations": 18338,
"inputs": [
{
"boxId": "ac60edc94d5ad83776da5f241ea5ff961660e57075c98edd8825f096ea2e09a9",
"value": 53000000,
"index": 0,
"spendingProof": "bbe8f1609cd275be6d098126135c2703e8aa6f66d2208a34898cb4e7d2555198981912f4abc56258d0ea4ba369451e9aa9c5b36858232f58",
"outputBlockId": "cac813a1f657a41ce8fff8a476889df6f2a6a8577e03d562cda7f6574eedc95c",
"outputTransactionId": "683d78de98524e013b3fd0b9ad6966f60a2184a24bd439283ffca3c2e91f26c2",
"outputIndex": 1,
"outputGlobalIndex": 54166471,
"outputCreatedAt": 1743200,
"outputSettledAt": 1743201,
"ergoTree": "1058040004000e20b0a0595bc2d5993f301d5dd85e8e17403d4df634b7b31e5b3e44066724eb566d0400040604000400040006072386f26fc10000040004000e20350a2e03c403508b12895dacf833e038a0d693128485522fb884caeb23d5990d040004020e20089990451bb430f05a85f4ef3bcb6ebf852b3d6ee68d86d78658b9ccef20074f040004000402040a040e04040400044004400450040c04d00f040004000400040004000402040404000400040004020400041004000410040004020580dac40904020580897a04d00f04d00f0400040004000580897a0580dac409050a0580897a0580dac409058084af5f058084af5f058084af5f04000402040604040406040a040c040e04d00f0402040205c0d0770580897a0601010400040004000400040104020402058092f401040004000400010104000580897ad837d601e4c6a7070ed602b5a5d9010263d801d604db63087202ed91b172047300938cb27204730100017201d603c2a7d6047302d605b5a4d901056393c272057203d606dc0c1a720502a77303d607e4c6a70911d608b27207730400d609db6308a7d60ab27209730500d60b8c720a01d60ce4c6a7040ed60de4c6a70507d60ee4c6a70605d60fe4c6a7080ed610c1a7d611d9011163d802d613c27211d61493721372037214d612b5a57211d613b27212720601a7d614db63087213d615b27214730600d6168c721502d617dc0c1aa402a77307d6187308d619e4c6b2b5db6501fed9011963d801d61bdb63087219ed91b1721b7309938cb2721b730a0001730b730c000506d61a8c720a02d61b7e721a06d61cb47209730db17209d61d730ed61ed9011e63d803d620c2721ed621cb7220d62293722172047222d61fb5a5721ed620b2721f721701a7d621db63087220d622b27221730f00d623b27207731000d624b17205d6259372247311d6267ea305d627b27207731200d628b27207731300d6299a72277228d62ab27207731400d62bb4720f73157316d62cb4720f73177318d62db27207731900d62e9d9c721b72197218d62f958f72267229d801d62f731a9d9c722e9a7e722d067e722f067e722f06722ed630b2721f731b01a7d631db63087230d632b27231731c00d633d9013363d803d635c27233d636cb7235d63793723672047237d634b5a57233d635b27234731d01a7d636db63087235d637b27236731e009591b17202731fd809d6387211d6397212d63ab17239d63b721ed63c721fd63db27202720601a7d63ee4c6723d0411d63fb2723e732000d640b2723e7321009591723a7322d80dd6417213d64293dc0c1aada5d9014263c5724202c57241732399b2e4c6723d09107324007325d643c17241d6447214d6457215d646e4c67241040ed647e4c672410507d648e4c67241070ed649edededed9272437208938c724501720b937246720c937247720d9372487201d64ae4c67241080ed64be4c672410605d64ce4c672410911d64d93b4724c73267327b47207732873299591b1723c732ad805d64e7e721606d64f7220d6507221d651b27250732b00d6527222d1ededededededededededededed7249724293720f724a92724372109072439a7210732c92724e99721b9d9c7e8c725102067218721993b47244732db17244721c93724b720e724deded92c1724f732e938c725201720b938c725101721d938c72520299721a7216927e723f069d9c9d9c724e721972187e7223067e732f0672259272267229d805d64e7e723f06d64f7330d6509d9c9d9c7e721606721972187e7223067e724f06d65192724e7250d652eb02d191b1b5a4d9015263d801d654db63087252eded91b172547331938cb2725473320001722b93b2e4c67252091a721700722c7333cd720deb02eb02eb02d1edededededededededed7249724293720f724a92724399721073349072439a72107335937244720991724b9a7226722a8f724b9a9a7226722a73368f724e7250724d7225d1edededededededededed7249724293720f724a92724399721073379072439a72107338937244720994720e733993724b733a7251724d7225ea027252d1ededededededededededededed7249724293720f724a92724e9d9c722f7e7240067e724f06937245720a93724b733b7251ed93b2724c733c00724093b2724c733d00b2723e733e00937224723a93b2724c733f00722a93b2724c734000720893b2724c734100722793b2724c734200722d93b2724c7343007228ea027252d1ededededededed724993724372109372447209937246720c937247720d937248720193724c7207937224723ad80bd6417e723f06d6427344d6437230d6447231d6457232d646b27244734500d647c5a7d648997241722fd6497eb2720773460006d64a9d9c7248997e72420672497e724206d64b8c724602d1edededededeced9072419d9c722f7e7223067e724206927226720e9172269a7e8cc7a701057347ededed92c172437348938c724501720b938c724601721d94c572437247938c724502721a958f724a7349927e724b067241d802d64cb2b5a5d9014c6393c2724c720c734a01a7d64db2db6308724c734b00ededed927e724b069a722f9d9c724872497e724206927e8c724d0206724a938c724d01721d94c5724c724793dc0c1aada4d9014c63c5724c027247734c999cb2e4c6723d0910734d00734e734f7225d806d6387233d6397234d63a7235d63b7236d63c7237d63db2723b735000d1ededededededed92c1723a7351938c723c01720b938c723d01721d94c5723ac5a7938c723c02721a917e8c723d0206722f9591b1b5a4d9013e63d801d640db6308723eeded91b172407352938cb2724073530001722b93b2e4c6723e091a721700722c73547355d801d63eb2b5a5d9013e6393c2723e720c735601a7eded92c1723e997210735793db6308723e721c94c5723ec5a77225",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-80,-96,89,91,-62,-43,-103,63,48,29,93,-40,94,-114,23,64,61,77,-10,52,-73,-77,30,91,62,68,6,103,36,-21,86,109)\n3: 0\n4: 3\n5: 0\n6: 0\n7: 0\n8: CBigInt(10000000000000000)\n9: 0\n10: 0\n11: Coll(53,10,46,3,-60,3,80,-117,18,-119,93,-84,-8,51,-32,56,-96,-42,-109,18,-124,-123,82,47,-72,-124,-54,-21,35,-43,-103,13)\n12: 0\n13: 1\n14: Coll(8,-103,-112,69,27,-76,48,-16,90,-123,-12,-17,59,-53,110,-65,-123,43,61,110,-26,-115,-122,-41,-122,88,-71,-52,-17,32,7,79)\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 0\n22: 32\n23: 32\n24: 40\n25: 6\n26: 1000\n27: 0\n28: 0\n29: 0\n30: 0\n31: 0\n32: 1\n33: 2\n34: 0\n35: 0\n36: 0\n37: 1\n38: 0\n39: 8\n40: 0\n41: 8\n42: 0\n43: 1\n44: 10000000\n45: 1\n46: 1000000\n47: 1000\n48: 1000\n49: 0\n50: 0\n51: 0\n52: 1000000\n53: 10000000\n54: 5\n55: 1000000\n56: 10000000\n57: 100000000\n58: 100000000\n59: 100000000\n60: 0\n61: 1\n62: 3\n63: 2\n64: 3\n65: 5\n66: 6\n67: 7\n68: 1000\n69: 1\n70: 1\n71: 980000\n72: 1000000\n73: CBigInt(1)\n74: 0\n75: 0\n76: 0\n77: 0\n78: -1\n79: 1\n80: 1\n81: 2000000\n82: 0\n83: 0\n84: 0\n85: true\n86: 0\n87: 1000000",
"ergoTreeScript": "{\n val coll1 = SELF.R7[Coll[Byte]].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == coll1)\n })\n val coll3 = SELF.propositionBytes\n val coll4 = placeholder[Coll[Byte]](2)\n val coll5 = INPUTS.filter({(box5: Box) => box5.propositionBytes == coll3 })\n val i6 = coll5.indexOf(SELF, placeholder[Int](3))\n val coll7 = SELF.R9[Coll[Long]].get\n val l8 = coll7(placeholder[Int](4))\n val coll9 = SELF.tokens\n val tuple10 = coll9(placeholder[Int](5))\n val coll11 = tuple10._1\n val coll12 = SELF.R4[Coll[Byte]].get\n val ge13 = SELF.R5[GroupElement].get\n val l14 = SELF.R6[Long].get\n val coll15 = SELF.R8[Coll[Byte]].get\n val l16 = SELF.value\n val func17 = {(box17: Box) =>\n val coll19 = box17.propositionBytes\n val bool20 = coll19 == coll3\n bool20\n }\n val coll18 = OUTPUTS.filter(func17)\n val box19 = coll18.getOrElse(i6, SELF)\n val coll20 = box19.tokens\n val tuple21 = coll20(placeholder[Int](6))\n val l22 = tuple21._2\n val i23 = INPUTS.indexOf(SELF, placeholder[Int](7))\n val bi24 = placeholder[BigInt](8)\n val bi25 = CONTEXT.dataInputs.filter({(box25: Box) =>\n val coll27 = box25.tokens\n (coll27.size > placeholder[Int](9)) && (coll27(placeholder[Int](10))._1 == placeholder[Coll[Byte]](11))\n })(placeholder[Int](12)).R5[BigInt].get\n val l26 = tuple10._2\n val bi27 = l26.toBigInt\n val coll28 = coll9.slice(placeholder[Int](13), coll9.size)\n val coll29 = placeholder[Coll[Byte]](14)\n val func30 = {(box30: Box) =>\n val coll32 = box30.propositionBytes\n val coll33 = blake2b256(coll32)\n val bool34 = coll33 == coll4\n bool34\n }\n val coll31 = OUTPUTS.filter(func30)\n val box32 = coll31.getOrElse(i23, SELF)\n val coll33 = box32.tokens\n val tuple34 = coll33(placeholder[Int](15))\n val l35 = coll7(placeholder[Int](16))\n val i36 = coll5.size\n val bool37 = i36 == placeholder[Int](17)\n val l38 = HEIGHT.toLong\n val l39 = coll7(placeholder[Int](18))\n val l40 = coll7(placeholder[Int](19))\n val l41 = l39 + l40\n val l42 = coll7(placeholder[Int](20))\n val coll43 = coll15.slice(placeholder[Int](21), placeholder[Int](22))\n val coll44 = coll15.slice(placeholder[Int](23), placeholder[Int](24))\n val l45 = coll7(placeholder[Int](25))\n val bi46 = bi27 * bi25 / bi24\n val bi47 = if (l38 < l41) {(\n val i47 = placeholder[Int](26)\n bi46 * l45.toBigInt + i47.toBigInt / i47.toBigInt\n )} else { bi46 }\n val box48 = coll31.getOrElse(placeholder[Int](27), SELF)\n val coll49 = box48.tokens\n val tuple50 = coll49(placeholder[Int](28))\n val func51 = {(box51: Box) =>\n val coll53 = box51.propositionBytes\n val coll54 = blake2b256(coll53)\n val bool55 = coll54 == coll4\n bool55\n }\n val coll52 = OUTPUTS.filter(func51)\n val box53 = coll52.getOrElse(placeholder[Int](29), SELF)\n val coll54 = box53.tokens\n val tuple55 = coll54(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func56 = func17\n val coll57 = coll18\n val i58 = coll57.size\n val func59 = func30\n val coll60 = coll31\n val box61 = coll2.getOrElse(i6, SELF)\n val coll62 = box61.R4[Coll[Long]].get\n val l63 = coll62(placeholder[Int](32))\n val l64 = coll62(placeholder[Int](33))\n if (i58 > placeholder[Int](34)) {(\n val box65 = box19\n val bool66 = OUTPUTS.map({(box66: Box) => box66.id }).indexOf(box65.id, placeholder[Int](35)) == box61.R9[Coll[Int]].get(\n placeholder[Int](36)\n ) - placeholder[Int](37)\n val l67 = box65.value\n val coll68 = coll20\n val tuple69 = tuple21\n val coll70 = box65.R4[Coll[Byte]].get\n val ge71 = box65.R5[GroupElement].get\n val coll72 = box65.R7[Coll[Byte]].get\n val bool73 = ((((l67 >= l8) && (tuple69._1 == coll11)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)\n val coll74 = box65.R8[Coll[Byte]].get\n val l75 = box65.R6[Long].get\n val coll76 = box65.R9[Coll[Long]].get\n val bool77 = coll76.slice(placeholder[Int](38), placeholder[Int](39)) == coll7.slice(placeholder[Int](40), placeholder[Int](41))\n if (coll60.size > placeholder[Int](42)) {(\n val bi78 = l22.toBigInt\n val box79 = box32\n val coll80 = coll33\n val tuple81 = coll80(placeholder[Int](43))\n val tuple82 = tuple34\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16)) && (l67 <= l16 + placeholder[Long](44))) && (\n bi78 >= bi27 - tuple81._2.toBigInt * bi24 / bi25\n )\n ) && (coll68.slice(placeholder[Int](45), coll68.size) == coll28)\n ) && (l75 == l14)\n ) && bool77\n ) && (((box79.value >= placeholder[Long](46)) && (tuple82._1 == coll11)) && (tuple81._1 == coll29))\n ) && (tuple82._2 == l26 - l22)\n ) && (l63.toBigInt >= bi78 * bi25 / bi24 * l35.toBigInt / placeholder[Int](47).toBigInt)\n ) && bool37\n ) && (l38 >= l41)\n )\n )} else {(\n val bi78 = l63.toBigInt\n val i79 = placeholder[Int](48)\n val bi80 = l22.toBigInt * bi25 / bi24 * l35.toBigInt / i79.toBigInt\n val bool81 = bi78 >= bi80\n val prop82 = sigmaProp(INPUTS.filter({(box82: Box) =>\n val coll84 = box82.tokens\n ((coll84.size > placeholder[Int](49)) && (coll84(placeholder[Int](50))._1 == coll43)) && (box82.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n }).size > placeholder[Int](51)) || proveDlog(ge13)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](52))) && (l67 <= l16 + placeholder[Long](53))) && (\n coll68 == coll9\n )\n ) && (l75 > l38 + l42)\n ) && (l75 < l38 + l42 + placeholder[Long](54))\n ) && (bi78 < bi80)\n ) && bool77\n ) && bool37\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](55))) && (l67 <= l16 + placeholder[Long](56))) && (\n coll68 == coll9\n )\n ) && (l14 != placeholder[Long](57))\n ) && (l75 == placeholder[Long](58))\n ) && bool81\n ) && bool77\n ) && bool37\n ) || prop82 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll15 == coll74)) && (bi78 >= bi47 * l64.toBigInt / i79.toBigInt)) && (tuple69 == tuple10)) && (\n l75 == placeholder[Long](59)\n )\n ) && bool81\n ) && ((coll76(placeholder[Int](60)) == l64) && (coll76(placeholder[Int](61)) == coll62(placeholder[Int](62))))\n ) && (i36 == i58)\n ) && (coll76(placeholder[Int](63)) == l42)\n ) && (coll76(placeholder[Int](64)) == l8)\n ) && (coll76(placeholder[Int](65)) == l39)\n ) && (coll76(placeholder[Int](66)) == l45)\n ) && (coll76(placeholder[Int](67)) == l40)\n ) || prop82 && sigmaProp(\n ((((((bool73 && (l67 == l16)) && (coll68 == coll9)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)) && (coll76 == coll7)) && (\n i36 == i58\n )\n )\n )}\n )} else {(\n val bi65 = l63.toBigInt\n val i66 = placeholder[Int](68)\n val box67 = box48\n val coll68 = coll49\n val tuple69 = tuple50\n val tuple70 = coll68(placeholder[Int](69))\n val coll71 = SELF.id\n val bi72 = bi65 - bi47\n val bi73 = coll7(placeholder[Int](70)).toBigInt\n val bi74 = bi72 * i66.toBigInt - bi73 / i66.toBigInt\n val l75 = tuple70._2\n sigmaProp(\n (\n (\n (\n (\n (((bi65 <= bi47 * l35.toBigInt / i66.toBigInt) && (l38 >= l14)) || (l38 > SELF.creationInfo._1.toLong + placeholder[Long](71))) && (\n (((box67.value >= placeholder[Long](72)) && (tuple69._1 == coll11)) && (tuple70._1 == coll29)) && (box67.id != coll71)\n )\n ) && (tuple69._2 == l26)\n ) && if (bi74 < placeholder[BigInt](73)) { l75.toBigInt >= bi65 } else {(\n val box76 = OUTPUTS.filter({(box76: Box) => box76.propositionBytes == coll12 }).getOrElse(placeholder[Int](74), SELF)\n val tuple77 = box76.tokens(placeholder[Int](75))\n (((l75.toBigInt >= bi47 + bi72 * bi73 / i66.toBigInt) && (tuple77._2.toBigInt >= bi74)) && (tuple77._1 == coll29)) && (box76.id != coll71)\n )}\n ) && (\n INPUTS.map({(box76: Box) => box76.id }).indexOf(coll71, placeholder[Int](76)) == box61.R9[Coll[Int]].get(placeholder[Int](77)) * placeholder[Int](\n 78\n ) - placeholder[Int](79)\n )\n ) && bool37\n )\n )}\n )} else {(\n val func56 = func51\n val coll57 = coll52\n val box58 = box53\n val coll59 = coll54\n val tuple60 = tuple55\n val tuple61 = coll59(placeholder[Int](80))\n sigmaProp(\n (\n (\n (\n ((((box58.value >= placeholder[Long](81)) && (tuple60._1 == coll11)) && (tuple61._1 == coll29)) && (box58.id != SELF.id)) && (tuple60._2 == l26)\n ) && (tuple61._2.toBigInt > bi47)\n ) && if (INPUTS.filter({(box62: Box) =>\n val coll64 = box62.tokens\n ((coll64.size > placeholder[Int](82)) && (coll64(placeholder[Int](83))._1 == coll43)) && (box62.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n }).size > placeholder[Int](84)) { placeholder[Boolean](85) } else {(\n val box62 = OUTPUTS.filter({(box62: Box) => box62.propositionBytes == coll12 }).getOrElse(placeholder[Int](86), SELF)\n ((box62.value >= l16 - placeholder[Long](87)) && (box62.tokens == coll28)) && (box62.id != SELF.id)\n )}\n ) && bool37\n )\n )}\n}",
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"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "04ca0f",
"sigmaType": "SInt",
"renderedValue": "997"
}
}
}
],
"outputs": [
{
"boxId": "070bf08a23e9870018cdcf12fe91ce0180b6fbcfc1aa7465e689f7ea9962655f",
"transactionId": "aefb9ce137e864c8bfc441b5a2c922dc9eb446b8aadfe2995d47928755cea4ce",
"blockId": "d7b26db8a0a8f0722a40ac379267a88d2055813ff1a1d7b3f2d00caf33002d2b",
"value": 53000000,
"index": 0,
"globalIndex": 54166692,
"creationHeight": 1743210,
"settlementHeight": 1743211,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-80,-96,89,91,-62,-43,-103,63,48,29,93,-40,94,-114,23,64,61,77,-10,52,-73,-77,30,91,62,68,6,103,36,-21,86,109)\n3: 0\n4: 3\n5: 0\n6: 0\n7: 0\n8: CBigInt(10000000000000000)\n9: 0\n10: 0\n11: Coll(53,10,46,3,-60,3,80,-117,18,-119,93,-84,-8,51,-32,56,-96,-42,-109,18,-124,-123,82,47,-72,-124,-54,-21,35,-43,-103,13)\n12: 0\n13: 1\n14: Coll(8,-103,-112,69,27,-76,48,-16,90,-123,-12,-17,59,-53,110,-65,-123,43,61,110,-26,-115,-122,-41,-122,88,-71,-52,-17,32,7,79)\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 0\n22: 32\n23: 32\n24: 40\n25: 6\n26: 1000\n27: 0\n28: 0\n29: 0\n30: 0\n31: 0\n32: 1\n33: 2\n34: 0\n35: 0\n36: 0\n37: 1\n38: 0\n39: 8\n40: 0\n41: 8\n42: 0\n43: 1\n44: 10000000\n45: 1\n46: 1000000\n47: 1000\n48: 1000\n49: 0\n50: 0\n51: 0\n52: 1000000\n53: 10000000\n54: 5\n55: 1000000\n56: 10000000\n57: 100000000\n58: 100000000\n59: 100000000\n60: 0\n61: 1\n62: 3\n63: 2\n64: 3\n65: 5\n66: 6\n67: 7\n68: 1000\n69: 1\n70: 1\n71: 980000\n72: 1000000\n73: CBigInt(1)\n74: 0\n75: 0\n76: 0\n77: 0\n78: -1\n79: 1\n80: 1\n81: 2000000\n82: 0\n83: 0\n84: 0\n85: true\n86: 0\n87: 1000000",
"ergoTreeScript": "{\n val coll1 = SELF.R7[Coll[Byte]].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == coll1)\n })\n val coll3 = SELF.propositionBytes\n val coll4 = placeholder[Coll[Byte]](2)\n val coll5 = INPUTS.filter({(box5: Box) => box5.propositionBytes == coll3 })\n val i6 = coll5.indexOf(SELF, placeholder[Int](3))\n val coll7 = SELF.R9[Coll[Long]].get\n val l8 = coll7(placeholder[Int](4))\n val coll9 = SELF.tokens\n val tuple10 = coll9(placeholder[Int](5))\n val coll11 = tuple10._1\n val coll12 = SELF.R4[Coll[Byte]].get\n val ge13 = SELF.R5[GroupElement].get\n val l14 = SELF.R6[Long].get\n val coll15 = SELF.R8[Coll[Byte]].get\n val l16 = SELF.value\n val func17 = {(box17: Box) =>\n val coll19 = box17.propositionBytes\n val bool20 = coll19 == coll3\n bool20\n }\n val coll18 = OUTPUTS.filter(func17)\n val box19 = coll18.getOrElse(i6, SELF)\n val coll20 = box19.tokens\n val tuple21 = coll20(placeholder[Int](6))\n val l22 = tuple21._2\n val i23 = INPUTS.indexOf(SELF, placeholder[Int](7))\n val bi24 = placeholder[BigInt](8)\n val bi25 = CONTEXT.dataInputs.filter({(box25: Box) =>\n val coll27 = box25.tokens\n (coll27.size > placeholder[Int](9)) && (coll27(placeholder[Int](10))._1 == placeholder[Coll[Byte]](11))\n })(placeholder[Int](12)).R5[BigInt].get\n val l26 = tuple10._2\n val bi27 = l26.toBigInt\n val coll28 = coll9.slice(placeholder[Int](13), coll9.size)\n val coll29 = placeholder[Coll[Byte]](14)\n val func30 = {(box30: Box) =>\n val coll32 = box30.propositionBytes\n val coll33 = blake2b256(coll32)\n val bool34 = coll33 == coll4\n bool34\n }\n val coll31 = OUTPUTS.filter(func30)\n val box32 = coll31.getOrElse(i23, SELF)\n val coll33 = box32.tokens\n val tuple34 = coll33(placeholder[Int](15))\n val l35 = coll7(placeholder[Int](16))\n val i36 = coll5.size\n val bool37 = i36 == placeholder[Int](17)\n val l38 = HEIGHT.toLong\n val l39 = coll7(placeholder[Int](18))\n val l40 = coll7(placeholder[Int](19))\n val l41 = l39 + l40\n val l42 = coll7(placeholder[Int](20))\n val coll43 = coll15.slice(placeholder[Int](21), placeholder[Int](22))\n val coll44 = coll15.slice(placeholder[Int](23), placeholder[Int](24))\n val l45 = coll7(placeholder[Int](25))\n val bi46 = bi27 * bi25 / bi24\n val bi47 = if (l38 < l41) {(\n val i47 = placeholder[Int](26)\n bi46 * l45.toBigInt + i47.toBigInt / i47.toBigInt\n )} else { bi46 }\n val box48 = coll31.getOrElse(placeholder[Int](27), SELF)\n val coll49 = box48.tokens\n val tuple50 = coll49(placeholder[Int](28))\n val func51 = {(box51: Box) =>\n val coll53 = box51.propositionBytes\n val coll54 = blake2b256(coll53)\n val bool55 = coll54 == coll4\n bool55\n }\n val coll52 = OUTPUTS.filter(func51)\n val box53 = coll52.getOrElse(placeholder[Int](29), SELF)\n val coll54 = box53.tokens\n val tuple55 = coll54(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func56 = func17\n val coll57 = coll18\n val i58 = coll57.size\n val func59 = func30\n val coll60 = coll31\n val box61 = coll2.getOrElse(i6, SELF)\n val coll62 = box61.R4[Coll[Long]].get\n val l63 = coll62(placeholder[Int](32))\n val l64 = coll62(placeholder[Int](33))\n if (i58 > placeholder[Int](34)) {(\n val box65 = box19\n val bool66 = OUTPUTS.map({(box66: Box) => box66.id }).indexOf(box65.id, placeholder[Int](35)) == box61.R9[Coll[Int]].get(\n placeholder[Int](36)\n ) - placeholder[Int](37)\n val l67 = box65.value\n val coll68 = coll20\n val tuple69 = tuple21\n val coll70 = box65.R4[Coll[Byte]].get\n val ge71 = box65.R5[GroupElement].get\n val coll72 = box65.R7[Coll[Byte]].get\n val bool73 = ((((l67 >= l8) && (tuple69._1 == coll11)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)\n val coll74 = box65.R8[Coll[Byte]].get\n val l75 = box65.R6[Long].get\n val coll76 = box65.R9[Coll[Long]].get\n val bool77 = coll76.slice(placeholder[Int](38), placeholder[Int](39)) == coll7.slice(placeholder[Int](40), placeholder[Int](41))\n if (coll60.size > placeholder[Int](42)) {(\n val bi78 = l22.toBigInt\n val box79 = box32\n val coll80 = coll33\n val tuple81 = coll80(placeholder[Int](43))\n val tuple82 = tuple34\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16)) && (l67 <= l16 + placeholder[Long](44))) && (\n bi78 >= bi27 - tuple81._2.toBigInt * bi24 / bi25\n )\n ) && (coll68.slice(placeholder[Int](45), coll68.size) == coll28)\n ) && (l75 == l14)\n ) && bool77\n ) && (((box79.value >= placeholder[Long](46)) && (tuple82._1 == coll11)) && (tuple81._1 == coll29))\n ) && (tuple82._2 == l26 - l22)\n ) && (l63.toBigInt >= bi78 * bi25 / bi24 * l35.toBigInt / placeholder[Int](47).toBigInt)\n ) && bool37\n ) && (l38 >= l41)\n )\n )} else {(\n val bi78 = l63.toBigInt\n val i79 = placeholder[Int](48)\n val bi80 = l22.toBigInt * bi25 / bi24 * l35.toBigInt / i79.toBigInt\n val bool81 = bi78 >= bi80\n val prop82 = sigmaProp(INPUTS.filter({(box82: Box) =>\n val coll84 = box82.tokens\n ((coll84.size > placeholder[Int](49)) && (coll84(placeholder[Int](50))._1 == coll43)) && (box82.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n }).size > placeholder[Int](51)) || proveDlog(ge13)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](52))) && (l67 <= l16 + placeholder[Long](53))) && (\n coll68 == coll9\n )\n ) && (l75 > l38 + l42)\n ) && (l75 < l38 + l42 + placeholder[Long](54))\n ) && (bi78 < bi80)\n ) && bool77\n ) && bool37\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](55))) && (l67 <= l16 + placeholder[Long](56))) && (\n coll68 == coll9\n )\n ) && (l14 != placeholder[Long](57))\n ) && (l75 == placeholder[Long](58))\n ) && bool81\n ) && bool77\n ) && bool37\n ) || prop82 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll15 == coll74)) && (bi78 >= bi47 * l64.toBigInt / i79.toBigInt)) && (tuple69 == tuple10)) && (\n l75 == placeholder[Long](59)\n )\n ) && bool81\n ) && ((coll76(placeholder[Int](60)) == l64) && (coll76(placeholder[Int](61)) == coll62(placeholder[Int](62))))\n ) && (i36 == i58)\n ) && (coll76(placeholder[Int](63)) == l42)\n ) && (coll76(placeholder[Int](64)) == l8)\n ) && (coll76(placeholder[Int](65)) == l39)\n ) && (coll76(placeholder[Int](66)) == l45)\n ) && (coll76(placeholder[Int](67)) == l40)\n ) || prop82 && sigmaProp(\n ((((((bool73 && (l67 == l16)) && (coll68 == coll9)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)) && (coll76 == coll7)) && (\n i36 == i58\n )\n )\n )}\n )} else {(\n val bi65 = l63.toBigInt\n val i66 = placeholder[Int](68)\n val box67 = box48\n val coll68 = coll49\n val tuple69 = tuple50\n val tuple70 = coll68(placeholder[Int](69))\n val coll71 = SELF.id\n val bi72 = bi65 - bi47\n val bi73 = coll7(placeholder[Int](70)).toBigInt\n val bi74 = bi72 * i66.toBigInt - bi73 / i66.toBigInt\n val l75 = tuple70._2\n sigmaProp(\n (\n (\n (\n (\n (((bi65 <= bi47 * l35.toBigInt / i66.toBigInt) && (l38 >= l14)) || (l38 > SELF.creationInfo._1.toLong + placeholder[Long](71))) && (\n (((box67.value >= placeholder[Long](72)) && (tuple69._1 == coll11)) && (tuple70._1 == coll29)) && (box67.id != coll71)\n )\n ) && (tuple69._2 == l26)\n ) && if (bi74 < placeholder[BigInt](73)) { l75.toBigInt >= bi65 } else {(\n val box76 = OUTPUTS.filter({(box76: Box) => box76.propositionBytes == coll12 }).getOrElse(placeholder[Int](74), SELF)\n val tuple77 = box76.tokens(placeholder[Int](75))\n (((l75.toBigInt >= bi47 + bi72 * bi73 / i66.toBigInt) && (tuple77._2.toBigInt >= bi74)) && (tuple77._1 == coll29)) && (box76.id != coll71)\n )}\n ) && (\n INPUTS.map({(box76: Box) => box76.id }).indexOf(coll71, placeholder[Int](76)) == box61.R9[Coll[Int]].get(placeholder[Int](77)) * placeholder[Int](\n 78\n ) - placeholder[Int](79)\n )\n ) && bool37\n )\n )}\n )} else {(\n val func56 = func51\n val coll57 = coll52\n val box58 = box53\n val coll59 = coll54\n val tuple60 = tuple55\n val tuple61 = coll59(placeholder[Int](80))\n sigmaProp(\n (\n (\n (\n ((((box58.value >= placeholder[Long](81)) && (tuple60._1 == coll11)) && (tuple61._1 == coll29)) && (box58.id != SELF.id)) && (tuple60._2 == l26)\n ) && (tuple61._2.toBigInt > bi47)\n ) && if (INPUTS.filter({(box62: Box) =>\n val coll64 = box62.tokens\n ((coll64.size > placeholder[Int](82)) && (coll64(placeholder[Int](83))._1 == coll43)) && (box62.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n }).size > placeholder[Int](84)) { placeholder[Boolean](85) } else {(\n val box62 = OUTPUTS.filter({(box62: Box) => box62.propositionBytes == coll12 }).getOrElse(placeholder[Int](86), SELF)\n ((box62.value >= l16 - placeholder[Long](87)) && (box62.tokens == coll28)) && (box62.id != SELF.id)\n )}\n ) && bool37\n )\n )}\n}",
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"sigmaType": "SLong",
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"R8": {
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"sigmaType": "Coll[SByte]",
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"sigmaType": "Coll[SByte]",
"renderedValue": "15ff840fa5f044fd04f37c6efa585582f2136024746bc818dc3cf6ae52991b9f"
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"sigmaType": "Coll[SLong]",
"renderedValue": "[1489,30,8,15000000,0,1743205,50,15]"
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"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
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"spentTransactionId": "472564526c3ffbe028f3dec167ca725d049c5a96e3843a0011da0cbfb4e20680",
"mainChain": true
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{
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"creationHeight": 1743210,
"settlementHeight": 1743211,
"ergoTree": "10020101048aba0cd1ed730091a37301",
"ergoTreeConstants": "0: true\n1: 102021",
"ergoTreeScript": "{sigmaProp(placeholder[Boolean](0) && (HEIGHT > placeholder[Int](1)))}",
"address": "BvWSwzcmLsqKxUY63sdXi1SdSQeL",
"assets": [
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"name": "Logic NFT ERG-2.0",
"decimals": 0,
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"R8": {
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"R7": {
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},
"R9": {
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"sigmaType": "Coll[SInt]",
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},
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"spentTransactionId": "472564526c3ffbe028f3dec167ca725d049c5a96e3843a0011da0cbfb4e20680",
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"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
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"name": "SigRSV",
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],
"additionalRegisters": {},
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{
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
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"type": "EIP-004"
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],
"additionalRegisters": {},
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{
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],
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}