Transaction
ID: 98e76f2cc0...f38e
Inputs (1)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0042 ERG
Tokens:
Loading assets...
Outputs (3)
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 852,826
Total coins transferred: 0.0042 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000261 ERG
Raw Transaction Data
{
"id": "98e76f2cc05961dd78e2b2486ff52cd685f836ee0106c3d048fceb9e4233f38e",
"blockId": "dd02e0c24827ed76898ac8399ea993f8f85c3c8e7251eece3bbc7a9682a4b3ae",
"inclusionHeight": 922547,
"timestamp": 1674239656616,
"index": 12,
"globalIndex": 4646130,
"numConfirmations": 852826,
"inputs": [
{
"boxId": "7d5ec86805699f5c09407546c372a04270f34bfdcd75eecb9458b0a2e7818149",
"value": 4200000,
"index": 0,
"spendingProof": null,
"outputBlockId": "dd02e0c24827ed76898ac8399ea993f8f85c3c8e7251eece3bbc7a9682a4b3ae",
"outputTransactionId": "9f9eb0db431864e24f618299887734a3e33424622bc07a8bd9baa80a950994e4",
"outputIndex": 0,
"outputGlobalIndex": 25805725,
"outputCreatedAt": 922545,
"outputSettledAt": 922547,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 3\n4: 2100000\n5: 1\n6: 0\n7: 0\n8: 2\n9: 0\n10: 7\n11: Coll(0,59,-47,-99,1,-121,17,127,19,11,98,-31,-68,-85,9,57,-110,-97,-11,-57,112,-97,-124,60,92,77,-47,88,-108,-110,-123,-48)\n12: Coll(48)\n13: 1\n14: 1\n15: false\n16: 1\n17: 1\n18: 0\n19: CBigInt(1000)\n20: 1\n21: 0\n22: CBigInt(1000000)\n23: 86400000\n24: 2\n25: 1\n26: 86400000\n27: 1\n28: 1\n29: 2\n30: 1\n31: 2100000\n32: 1\n33: 9\n34: false\n35: 14400000\n36: 2\n37: 0\n38: 0\n39: 2\n40: 1\n41: 0\n42: 0\n43: 0\n44: 100\n45: 500\n46: 1000\n47: 2000\n48: 4000\n49: 9000\n50: 13000\n51: 20000\n52: 30000\n53: 40000\n54: 50000\n55: 70000\n56: 110000\n57: 140000\n58: 170000\n59: 210000\n60: 250000\n61: 300000\n62: 500000\n63: 1000000\n64: 10000000\n65: 1\n66: 0\n67: 1\n68: 0\n69: 0\n70: 1\n71: CBigInt(1)\n72: CBigInt(0)\n73: 4\n74: 4\n75: 1775840000\n76: CBigInt(0)\n77: 5\n78: CBigInt(177584)\n79: 6\n80: 177584000\n81: 10000\n82: 0\n83: Coll(29,90,-4,89,-125,-119,32,-69,94,-14,-88,-7,-42,56,37,-91,91,29,72,-30,105,-41,-50,-50,-29,53,-42,55,-61,-1,95,63)\n84: 3\n85: 2\n86: 2\n87: 3\n88: 3\n89: 8\n90: false\n91: 2\n92: 4\n93: 0\n94: 1\n95: 0\n96: 2\n97: 0\n98: 0\n99: 1\n100: 0\n101: 0\n102: 1\n103: false\n104: 2100000\n105: 1\n106: 1\n107: 1100000\n108: false",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val tuple2 = (Coll[Byte](), placeholder[Long](0))\n val tuple3 = coll1.getOrElse(placeholder[Int](1), tuple2)\n val box4 = SELF.R7[Box].get\n val bool5 = (tuple3._1 == box4.id) && (SELF.propositionBytes == box4.propositionBytes)\n val box6 = if (bool5) { box4 } else { SELF }\n val prop7 = box6.R9[SigmaProp].get\n val bool8 = !bool5\n val box9 = OUTPUTS(placeholder[Int](2))\n val coll10 = box9.propositionBytes\n val coll11 = prop7.propBytes\n val bool12 = coll10 == coll11\n val coll13 = box6.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](3))\n val l15 = CONTEXT.preHeader.timestamp\n val l16 = l14 - l15\n val l17 = box9.value\n val bool18 = l17 >= placeholder[Long](4)\n val coll19 = box9.tokens\n val tuple20 = coll19.getOrElse(placeholder[Int](5), tuple2)\n val l21 = tuple20._2\n val l22 = tuple3._2\n val bool23 = coll13(placeholder[Int](6)) == placeholder[Long](7)\n val l24 = coll13(placeholder[Int](8))\n val tuple25 = coll19.getOrElse(placeholder[Int](9), tuple2)\n val l26 = tuple25._2\n val l27 = SELF.value\n val l28 = coll13(placeholder[Int](10))\n val coll29 = tuple25._1\n val coll30 = box6.id\n val coll31 = placeholder[Coll[Byte]](11)\n val coll32 = placeholder[Coll[Byte]](12)\n val bool33 = if (coll10 == SELF.propositionBytes) {\n (\n (\n (\n (\n (((coll29 == coll30) && (l26 >= placeholder[Long](13))) && bool18) && (\n ((bool23 && (tuple20._1 == coll31)) && (l21 >= placeholder[Long](14))) || (!bool23)\n )\n ) && (box9.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)\n ) && (box9.R5[Coll[Byte]].get == coll32)\n ) && (box9.R6[Coll[Byte]].get == coll32)\n ) && (box9.R7[Box].get == box6)\n } else { placeholder[Boolean](15) }\n val box34 = OUTPUTS(placeholder[Int](16))\n val coll35 = box6.R5[Coll[Byte]].get\n val bool36 = l15 <= l14\n val tuple37 = coll1.getOrElse(placeholder[Int](17), tuple2)\n val l38 = tuple37._2\n val coll39 = box34.tokens\n val tuple40 = coll39.getOrElse(placeholder[Int](18), tuple2)\n val coll41 = tuple40._1\n val l42 = tuple40._2\n val bi43 = placeholder[BigInt](19)\n val bool44 = coll13(placeholder[Int](20)) == placeholder[Long](21)\n val bi45 = placeholder[BigInt](22)\n val bool46 = l15 > l14\n val bool47 = if (bool44) { (bool5 && bool46) && (l15 < l14 + placeholder[Long](23)) } else { bool5 && bool36 }\n prop7 && sigmaProp((bool8 && (OUTPUTS.size == placeholder[Int](24))) && bool12) || sigmaProp(\n (\n (\n if ((bool8 && (INPUTS.size == placeholder[Int](25))) && (l16 >= placeholder[Long](26))) {\n (\n (\n bool33 && (\n (bool18 && (box9.R7[Box].get == SELF)) && (\n (\n ((bool23 && (l21 == l22)) && (l26 == l22 - placeholder[Long](27) / l24 + placeholder[Long](28))) && (coll19.size == placeholder[Int](29))\n ) || (((!bool23) && (coll19.size == placeholder[Int](30))) && (l26 == l27 - placeholder[Long](31) / l28 + placeholder[Long](32)))\n )\n )\n ) && (box34.propositionBytes == coll35)\n ) && (box34.value >= coll13(placeholder[Int](33)))\n } else { placeholder[Boolean](34) } || if (((!(bool36 && (l15 > l14 - placeholder[Long](35)))) && (INPUTS.size == placeholder[Int](36))) && (\n CONTEXT.dataInputs.size > placeholder[Int](37)\n )) {(\n val box48 = CONTEXT.dataInputs(placeholder[Int](38))\n val coll49 = box48.tokens\n val l50 = l22 - l26\n val l51 = box48.value / coll49(placeholder[Int](39))._2 / placeholder[Long](40)\n val l52 = if (bool23) { max(placeholder[Long](41), l51 - l28 * l24) } else { max(placeholder[Long](42), l28 - l51 * l24) }\n val coll53 = Coll[Long](\n placeholder[Long](43), placeholder[Long](44), placeholder[Long](45), placeholder[Long](46), placeholder[Long](47), placeholder[Long](\n 48\n ), placeholder[Long](49), placeholder[Long](50), placeholder[Long](51), placeholder[Long](52), placeholder[Long](53), placeholder[Long](\n 54\n ), placeholder[Long](55), placeholder[Long](56), placeholder[Long](57), placeholder[Long](58), placeholder[Long](59), placeholder[Long](\n 60\n ), placeholder[Long](61), placeholder[Long](62), placeholder[Long](63), placeholder[Long](64)\n )\n val coll54 = coll53.map({(l54: Long) => l54 * l54 }).zip(coll53)\n val func55 = {(l55: Long) =>\n val i57 = coll54.map({(tuple57: (Long, Long)) => if (tuple57._1 >= l55) { placeholder[Long](65) } else { placeholder[Long](66) } }).indexOf(\n placeholder[Long](67), placeholder[Int](68)\n )\n val tuple58 = coll54(i57)\n if (i57.toLong > placeholder[Long](69)) {(\n val tuple59 = coll54(i57 - placeholder[Int](70))\n val l60 = tuple59._2\n val l61 = tuple59._1\n max(placeholder[BigInt](71), l60.toBigInt + tuple58._2 - l60.toBigInt * l55 - l61.toBigInt / tuple58._1 - l61.toBigInt)\n )} else { placeholder[BigInt](72) }\n }\n val bi56 = func55(l16)\n val bi57 = placeholder[Long](73) * coll13(placeholder[Int](74)).toBigInt * l24.toBigInt * l28.toBigInt * bi56 / placeholder[Int](75).toBigInt\n val bi58 = max(\n placeholder[BigInt](76), bi57 - bi57 * coll13(placeholder[Int](77)).toBigInt * func55(max(l51 - l28, l28 - l51)) * placeholder[BigInt](\n 78\n ) / bi43 * func55(l28) * bi56\n )\n val bi59 = if (bool44) { l52.toBigInt + bi58 } else {\n l52.toBigInt + bi58 + bi58 * coll13(placeholder[Int](79)).toBigInt * bi56 / placeholder[Int](80).toBigInt\n }\n val bi60 = max(bi45, bi59 - bi59 % placeholder[Long](81).toBigInt)\n val bi61 = l50.toBigInt * if (bool23) { min(l51 * l24.toBigInt, bi60) } else { min(l28 * l24.toBigInt, bi60) }\n (\n (\n (\n (\n (\n (\n (\n (((coll49(placeholder[Int](82))._1 == placeholder[Coll[Byte]](83)) && (coll49(placeholder[Int](84))._1 == coll31)) && bool33) && (\n l17 == l27\n )\n ) && (l21 == l38)\n ) && (coll41 == coll30)\n ) && (l42 == l50)\n ) && (OUTPUTS(placeholder[Int](85)).propositionBytes == coll11)\n ) && (OUTPUTS(placeholder[Int](86)).value.toBigInt >= max(bi45, bi61))\n ) && (OUTPUTS(placeholder[Int](87)).propositionBytes == coll35)\n ) && (OUTPUTS(placeholder[Int](88)).value.toBigInt >= max(bi45, bi61 * coll13(placeholder[Int](89)).toBigInt / bi43))\n )} else { placeholder[Boolean](90) }\n ) || if (((bool47 && (INPUTS.size == placeholder[Int](91))) && (OUTPUTS.size == placeholder[Int](92))) && (\n CONTEXT.dataInputs.size == placeholder[Int](93)\n )) {(\n val l48 = if (bool23) { l38 - l21 } else { l27 - l17 }\n val l49 = if (bool23) { l48 / l24 } else { l48 / l28 * l24 }\n val tuple50 = INPUTS(placeholder[Int](94)).tokens.getOrElse(placeholder[Int](95), tuple2)\n val box51 = OUTPUTS(placeholder[Int](96))\n val coll52 = box51.tokens\n val tuple53 = coll52.getOrElse(placeholder[Int](97), tuple2)\n (\n (((l49 == if (tuple50._1 == coll30) { tuple50._2 } else { placeholder[Long](98) }) && bool33) && (l26 == l22)) && (\n (\n ((((bool23 && (coll41 == coll31)) && (l42 == l48)) && (coll39.size == placeholder[Int](99))) && (box51.value >= l49 * l28 * l24)) && (\n coll52.size == placeholder[Int](100)\n )\n ) || (\n (((((!bool23) && (box34.value >= l48)) && (coll39.size == placeholder[Int](101))) && (tuple53._1 == coll31)) && (tuple53._2 >= l49 * l24)) && (\n coll52.size == placeholder[Int](102)\n )\n )\n )\n ) && (box51.propositionBytes == coll11)\n )} else { placeholder[Boolean](103) }\n ) || if ((bool46 && (!bool47)) || (((l27 == placeholder[Long](104)) && (l22 == placeholder[Long](105))) && (l38 <= placeholder[Long](106)))) {\n ((bool12 && (l17 >= l27 - placeholder[Long](107))) && (coll29 == tuple37._1)) && (l26 == l38)\n } else { placeholder[Boolean](108) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 0,
"amount": 101,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e240008cd039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
"serializedValue": "110a0002c80180c0e291f461e807f80ac801c6dc3b0a80897a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,100,1682035200000,500,700,100,489251,5,1000000]"
},
"R7": {
"serializedValue": "63a0968001100205000502d19373007301e28f3800040e01200e01200e012063c0843d10010100d17300ce8f380000c29e8341fbb9884bc3c58559b49c529f5f9b2ff038b97f9e76976c92ba917b0f01bd0beef5b5e1eb164d6999d5d038f793954ebe93f82ea3bd0fa1b8c65edc41b100",
"sigmaType": null,
"renderedValue": null
},
"R9": {
"serializedValue": "08cd02c35a808c1c713fc1ae169e33da7492eee8f913a2045a7d56a3ca3103b5525ff3",
"sigmaType": "SSigmaProp",
"renderedValue": "02c35a808c1c713fc1ae169e33da7492eee8f913a2045a7d56a3ca3103b5525ff3"
},
"R4": {
"serializedValue": "0e2b43616c6c5f415f5369675253565f4552475f3438393235315f323032332d30342d32315f7065725f313030",
"sigmaType": "Coll[SByte]",
"renderedValue": "43616c6c5f415f5369675253565f4552475f3438393235315f323032332d30342d32315f7065725f313030"
}
}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "3d55af9c4ec0d04db25aa4f0f7e4095caf6b6aa89568f79225ee76a572cb12be",
"transactionId": "98e76f2cc05961dd78e2b2486ff52cd685f836ee0106c3d048fceb9e4233f38e",
"blockId": "dd02e0c24827ed76898ac8399ea993f8f85c3c8e7251eece3bbc7a9682a4b3ae",
"value": 2100000,
"index": 0,
"globalIndex": 25805728,
"creationHeight": 922545,
"settlementHeight": 922547,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 3\n4: 2100000\n5: 1\n6: 0\n7: 0\n8: 2\n9: 0\n10: 7\n11: Coll(0,59,-47,-99,1,-121,17,127,19,11,98,-31,-68,-85,9,57,-110,-97,-11,-57,112,-97,-124,60,92,77,-47,88,-108,-110,-123,-48)\n12: Coll(48)\n13: 1\n14: 1\n15: false\n16: 1\n17: 1\n18: 0\n19: CBigInt(1000)\n20: 1\n21: 0\n22: CBigInt(1000000)\n23: 86400000\n24: 2\n25: 1\n26: 86400000\n27: 1\n28: 1\n29: 2\n30: 1\n31: 2100000\n32: 1\n33: 9\n34: false\n35: 14400000\n36: 2\n37: 0\n38: 0\n39: 2\n40: 1\n41: 0\n42: 0\n43: 0\n44: 100\n45: 500\n46: 1000\n47: 2000\n48: 4000\n49: 9000\n50: 13000\n51: 20000\n52: 30000\n53: 40000\n54: 50000\n55: 70000\n56: 110000\n57: 140000\n58: 170000\n59: 210000\n60: 250000\n61: 300000\n62: 500000\n63: 1000000\n64: 10000000\n65: 1\n66: 0\n67: 1\n68: 0\n69: 0\n70: 1\n71: CBigInt(1)\n72: CBigInt(0)\n73: 4\n74: 4\n75: 1775840000\n76: CBigInt(0)\n77: 5\n78: CBigInt(177584)\n79: 6\n80: 177584000\n81: 10000\n82: 0\n83: Coll(29,90,-4,89,-125,-119,32,-69,94,-14,-88,-7,-42,56,37,-91,91,29,72,-30,105,-41,-50,-50,-29,53,-42,55,-61,-1,95,63)\n84: 3\n85: 2\n86: 2\n87: 3\n88: 3\n89: 8\n90: false\n91: 2\n92: 4\n93: 0\n94: 1\n95: 0\n96: 2\n97: 0\n98: 0\n99: 1\n100: 0\n101: 0\n102: 1\n103: false\n104: 2100000\n105: 1\n106: 1\n107: 1100000\n108: false",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val tuple2 = (Coll[Byte](), placeholder[Long](0))\n val tuple3 = coll1.getOrElse(placeholder[Int](1), tuple2)\n val box4 = SELF.R7[Box].get\n val bool5 = (tuple3._1 == box4.id) && (SELF.propositionBytes == box4.propositionBytes)\n val box6 = if (bool5) { box4 } else { SELF }\n val prop7 = box6.R9[SigmaProp].get\n val bool8 = !bool5\n val box9 = OUTPUTS(placeholder[Int](2))\n val coll10 = box9.propositionBytes\n val coll11 = prop7.propBytes\n val bool12 = coll10 == coll11\n val coll13 = box6.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](3))\n val l15 = CONTEXT.preHeader.timestamp\n val l16 = l14 - l15\n val l17 = box9.value\n val bool18 = l17 >= placeholder[Long](4)\n val coll19 = box9.tokens\n val tuple20 = coll19.getOrElse(placeholder[Int](5), tuple2)\n val l21 = tuple20._2\n val l22 = tuple3._2\n val bool23 = coll13(placeholder[Int](6)) == placeholder[Long](7)\n val l24 = coll13(placeholder[Int](8))\n val tuple25 = coll19.getOrElse(placeholder[Int](9), tuple2)\n val l26 = tuple25._2\n val l27 = SELF.value\n val l28 = coll13(placeholder[Int](10))\n val coll29 = tuple25._1\n val coll30 = box6.id\n val coll31 = placeholder[Coll[Byte]](11)\n val coll32 = placeholder[Coll[Byte]](12)\n val bool33 = if (coll10 == SELF.propositionBytes) {\n (\n (\n (\n (\n (((coll29 == coll30) && (l26 >= placeholder[Long](13))) && bool18) && (\n ((bool23 && (tuple20._1 == coll31)) && (l21 >= placeholder[Long](14))) || (!bool23)\n )\n ) && (box9.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)\n ) && (box9.R5[Coll[Byte]].get == coll32)\n ) && (box9.R6[Coll[Byte]].get == coll32)\n ) && (box9.R7[Box].get == box6)\n } else { placeholder[Boolean](15) }\n val box34 = OUTPUTS(placeholder[Int](16))\n val coll35 = box6.R5[Coll[Byte]].get\n val bool36 = l15 <= l14\n val tuple37 = coll1.getOrElse(placeholder[Int](17), tuple2)\n val l38 = tuple37._2\n val coll39 = box34.tokens\n val tuple40 = coll39.getOrElse(placeholder[Int](18), tuple2)\n val coll41 = tuple40._1\n val l42 = tuple40._2\n val bi43 = placeholder[BigInt](19)\n val bool44 = coll13(placeholder[Int](20)) == placeholder[Long](21)\n val bi45 = placeholder[BigInt](22)\n val bool46 = l15 > l14\n val bool47 = if (bool44) { (bool5 && bool46) && (l15 < l14 + placeholder[Long](23)) } else { bool5 && bool36 }\n prop7 && sigmaProp((bool8 && (OUTPUTS.size == placeholder[Int](24))) && bool12) || sigmaProp(\n (\n (\n if ((bool8 && (INPUTS.size == placeholder[Int](25))) && (l16 >= placeholder[Long](26))) {\n (\n (\n bool33 && (\n (bool18 && (box9.R7[Box].get == SELF)) && (\n (\n ((bool23 && (l21 == l22)) && (l26 == l22 - placeholder[Long](27) / l24 + placeholder[Long](28))) && (coll19.size == placeholder[Int](29))\n ) || (((!bool23) && (coll19.size == placeholder[Int](30))) && (l26 == l27 - placeholder[Long](31) / l28 + placeholder[Long](32)))\n )\n )\n ) && (box34.propositionBytes == coll35)\n ) && (box34.value >= coll13(placeholder[Int](33)))\n } else { placeholder[Boolean](34) } || if (((!(bool36 && (l15 > l14 - placeholder[Long](35)))) && (INPUTS.size == placeholder[Int](36))) && (\n CONTEXT.dataInputs.size > placeholder[Int](37)\n )) {(\n val box48 = CONTEXT.dataInputs(placeholder[Int](38))\n val coll49 = box48.tokens\n val l50 = l22 - l26\n val l51 = box48.value / coll49(placeholder[Int](39))._2 / placeholder[Long](40)\n val l52 = if (bool23) { max(placeholder[Long](41), l51 - l28 * l24) } else { max(placeholder[Long](42), l28 - l51 * l24) }\n val coll53 = Coll[Long](\n placeholder[Long](43), placeholder[Long](44), placeholder[Long](45), placeholder[Long](46), placeholder[Long](47), placeholder[Long](\n 48\n ), placeholder[Long](49), placeholder[Long](50), placeholder[Long](51), placeholder[Long](52), placeholder[Long](53), placeholder[Long](\n 54\n ), placeholder[Long](55), placeholder[Long](56), placeholder[Long](57), placeholder[Long](58), placeholder[Long](59), placeholder[Long](\n 60\n ), placeholder[Long](61), placeholder[Long](62), placeholder[Long](63), placeholder[Long](64)\n )\n val coll54 = coll53.map({(l54: Long) => l54 * l54 }).zip(coll53)\n val func55 = {(l55: Long) =>\n val i57 = coll54.map({(tuple57: (Long, Long)) => if (tuple57._1 >= l55) { placeholder[Long](65) } else { placeholder[Long](66) } }).indexOf(\n placeholder[Long](67), placeholder[Int](68)\n )\n val tuple58 = coll54(i57)\n if (i57.toLong > placeholder[Long](69)) {(\n val tuple59 = coll54(i57 - placeholder[Int](70))\n val l60 = tuple59._2\n val l61 = tuple59._1\n max(placeholder[BigInt](71), l60.toBigInt + tuple58._2 - l60.toBigInt * l55 - l61.toBigInt / tuple58._1 - l61.toBigInt)\n )} else { placeholder[BigInt](72) }\n }\n val bi56 = func55(l16)\n val bi57 = placeholder[Long](73) * coll13(placeholder[Int](74)).toBigInt * l24.toBigInt * l28.toBigInt * bi56 / placeholder[Int](75).toBigInt\n val bi58 = max(\n placeholder[BigInt](76), bi57 - bi57 * coll13(placeholder[Int](77)).toBigInt * func55(max(l51 - l28, l28 - l51)) * placeholder[BigInt](\n 78\n ) / bi43 * func55(l28) * bi56\n )\n val bi59 = if (bool44) { l52.toBigInt + bi58 } else {\n l52.toBigInt + bi58 + bi58 * coll13(placeholder[Int](79)).toBigInt * bi56 / placeholder[Int](80).toBigInt\n }\n val bi60 = max(bi45, bi59 - bi59 % placeholder[Long](81).toBigInt)\n val bi61 = l50.toBigInt * if (bool23) { min(l51 * l24.toBigInt, bi60) } else { min(l28 * l24.toBigInt, bi60) }\n (\n (\n (\n (\n (\n (\n (\n (((coll49(placeholder[Int](82))._1 == placeholder[Coll[Byte]](83)) && (coll49(placeholder[Int](84))._1 == coll31)) && bool33) && (\n l17 == l27\n )\n ) && (l21 == l38)\n ) && (coll41 == coll30)\n ) && (l42 == l50)\n ) && (OUTPUTS(placeholder[Int](85)).propositionBytes == coll11)\n ) && (OUTPUTS(placeholder[Int](86)).value.toBigInt >= max(bi45, bi61))\n ) && (OUTPUTS(placeholder[Int](87)).propositionBytes == coll35)\n ) && (OUTPUTS(placeholder[Int](88)).value.toBigInt >= max(bi45, bi61 * coll13(placeholder[Int](89)).toBigInt / bi43))\n )} else { placeholder[Boolean](90) }\n ) || if (((bool47 && (INPUTS.size == placeholder[Int](91))) && (OUTPUTS.size == placeholder[Int](92))) && (\n CONTEXT.dataInputs.size == placeholder[Int](93)\n )) {(\n val l48 = if (bool23) { l38 - l21 } else { l27 - l17 }\n val l49 = if (bool23) { l48 / l24 } else { l48 / l28 * l24 }\n val tuple50 = INPUTS(placeholder[Int](94)).tokens.getOrElse(placeholder[Int](95), tuple2)\n val box51 = OUTPUTS(placeholder[Int](96))\n val coll52 = box51.tokens\n val tuple53 = coll52.getOrElse(placeholder[Int](97), tuple2)\n (\n (((l49 == if (tuple50._1 == coll30) { tuple50._2 } else { placeholder[Long](98) }) && bool33) && (l26 == l22)) && (\n (\n ((((bool23 && (coll41 == coll31)) && (l42 == l48)) && (coll39.size == placeholder[Int](99))) && (box51.value >= l49 * l28 * l24)) && (\n coll52.size == placeholder[Int](100)\n )\n ) || (\n (((((!bool23) && (box34.value >= l48)) && (coll39.size == placeholder[Int](101))) && (tuple53._1 == coll31)) && (tuple53._2 >= l49 * l24)) && (\n coll52.size == placeholder[Int](102)\n )\n )\n )\n ) && (box51.propositionBytes == coll11)\n )} else { placeholder[Boolean](103) }\n ) || if ((bool46 && (!bool47)) || (((l27 == placeholder[Long](104)) && (l22 == placeholder[Long](105))) && (l38 <= placeholder[Long](106)))) {\n ((bool12 && (l17 >= l27 - placeholder[Long](107))) && (coll29 == tuple37._1)) && (l26 == l38)\n } else { placeholder[Boolean](108) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "7d5ec86805699f5c09407546c372a04270f34bfdcd75eecb9458b0a2e7818149",
"index": 0,
"amount": 2,
"name": "Call_A_SigRSV_ERG_489251_2023-04-21_per_100",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 1,
"amount": 101,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2b43616c6c5f415f5369675253565f4552475f3438393235315f323032332d30342d32315f7065725f313030",
"sigmaType": "Coll[SByte]",
"renderedValue": "43616c6c5f415f5369675253565f4552475f3438393235315f323032332d30342d32315f7065725f313030"
},
"R5": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
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},
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},
{
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"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(9ed9a6,83e77d,...)))}",
"address": "9hfmJjrmeyhNgQZks1NzvrJyNgtHuMinnZbrupk6gGxTZWQQf87",
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"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)}",
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}
],
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}