Transaction
ID: 387bd2db14...5f24
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
50.21 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00015 ERG
Tokens:
0
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00485 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
50.21 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 463,619
Total coins transferred: 50.22 ERG
Fees: 0.00485 ERG
Fees per byte: 0.000000266 ERG
Raw Transaction Data
{
"id": "387bd2db14877e281e08c9ee475fdd0b48b4df56d366d575c486822689e35f24",
"blockId": "ebb325effd7cfb17bbea9ba798a2a17755f1e7499f3f652ee981110987e89fd7",
"inclusionHeight": 1295020,
"timestamp": 1719412865978,
"index": 3,
"globalIndex": 7404243,
"numConfirmations": 463619,
"inputs": [
{
"boxId": "72c20e32aed965003fb9ea9f901e90c8bf46593ef521a6f13802b4a195791702",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "ebb325effd7cfb17bbea9ba798a2a17755f1e7499f3f652ee981110987e89fd7",
"outputTransactionId": "d4b2fcfb3bae6a74ce884837611fc55f255b411dcfdd36b5e900433cca42399f",
"outputIndex": 0,
"outputGlobalIndex": 41072591,
"outputCreatedAt": 1295018,
"outputSettledAt": 1295020,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: Coll(-34,-82,-49,91,100,-70,-42,-11,87,11,-83,10,97,12,78,72,73,87,-49,71,-126,48,-124,0,-68,-112,64,76,29,20,16,-38)\n3: Coll(3,-110,8,-68,78,-17,-102,3,-24,-41,-117,-122,99,-93,1,-69,95,-83,-36,-89,-117,-31,-99,127,-27,53,-77,-58,76,-66,-2,66)\n4: Coll(-120,48,97,44,82,53,95,111,40,13,18,-105,-15,-97,103,-80,120,-55,-38,-89,-41,-80,75,69,-100,-111,-52,100,73,87,-62,-128)\n5: Coll(-117,-57,-113,28,106,-82,-55,30,98,-114,21,-49,102,-116,22,-52,30,-101,-40,-28,-71,-73,-31,109,99,24,-75,-11,35,-91,-23,-67)\n6: Coll(79,-40,-80,-42,-39,-126,66,114,111,87,-77,-33,-90,-122,18,103,-110,-72,-27,5,110,29,81,-74,-23,13,104,-128,-49,45,-51,-59)\n7: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n8: Coll(58,17,-107,92,71,25,-27,-120,-68,-26,-89,97,29,39,-67,31,-33,-37,87,56,92,-82,-30,102,-40,4,12,-119,79,28,46,29)\n9: Coll(9,-126,15,-53,-120,113,-5,69,12,62,6,-73,-53,94,39,-80,69,80,-121,-93,102,98,26,-99,-34,117,-126,-96,25,17,30,62)\n10: 0\n11: 0\n12: Coll(56,-68,56,81,78,28,46,-125,35,35,15,64,-22,39,-43,43,-118,-49,66,82,8,-17,-118,10,-96,-7,-25,75,-28,27,28,-124)\n13: 0\n14: 6\n15: 0\n16: 1\n17: 1\n18: 33\n19: 1\n20: 2\n21: 1\n22: 33\n23: 2\n24: 3\n25: 1\n26: 33\n27: 3\n28: 4\n29: 1\n30: 33\n31: 4\n32: 5\n33: 1\n34: 33\n35: 5\n36: 6\n37: 1\n38: 33\n39: 6\n40: 7\n41: 1\n42: 33\n43: 0\n44: 1\n45: 33\n46: 0\n47: 0\n48: 1\n49: 1",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val b2 = getVar[Byte](1.toByte).get\n val i3 = b2.toInt\n val box4 = INPUTS(placeholder[Int](1))\n val coll5 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](\n placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4), placeholder[Coll[Byte]](5), placeholder[Coll[Byte]](6), placeholder[\n Coll[Byte]\n ](7), placeholder[Coll[Byte]](8), placeholder[Coll[Byte]](9)\n ), getVar[Coll[Byte]](0.toByte).get\n )\n val box6 = OUTPUTS(placeholder[Int](10))\n val coll7 = box6.tokens\n val coll8 = SELF.tokens\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), (i3 >= placeholder[Int](13)) && (i3 <= placeholder[Int](14)), anyOf(\n Coll[Boolean](\n (b2 == placeholder[Byte](15)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](16)).get.slice(placeholder[Int](17), placeholder[Int](18))\n ), (b2 == placeholder[Byte](19)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](20)).get.slice(placeholder[Int](21), placeholder[Int](22))\n ), (b2 == placeholder[Byte](23)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](24)).get.slice(placeholder[Int](25), placeholder[Int](26))\n ), (b2 == placeholder[Byte](27)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](28)).get.slice(placeholder[Int](29), placeholder[Int](30))\n ), (b2 == placeholder[Byte](31)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](32)).get.slice(placeholder[Int](33), placeholder[Int](34))\n ), (b2 == placeholder[Byte](35)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38))\n ), (b2 == placeholder[Byte](39)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](40)).get.slice(placeholder[Int](41), placeholder[Int](42))\n )\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box6.propositionBytes) == coll5(placeholder[Int](43)).get.slice(placeholder[Int](44), placeholder[Int](45)), coll7(\n placeholder[Int](46)\n ) == coll8(placeholder[Int](47)), coll7(placeholder[Int](48))._1 == coll8(placeholder[Int](49))._1\n )\n )\n )\n )\n )\n}",
"address": "MUeEFF9n6rMZGwhMHSCUToqgZV77SPd7enUFfdMSt9BwbM2eVwCQ44yZjJRqxpgU8bJijkTjNhB7AH2wUM9UkZjHnyPDKFRDMozra8a3ptKsKvQXN3wBzXAwBaTFpdS2WuYqQTP4VzokiUjFsoesobW74Nh51uAqDTXKK4SZ4QnphLpCAVPBu9rEca48RLrMViEzYQKchqzyX2oA7cSzY8do7poc4Y6jPiNYuRbLyjifcNBqBVjRruuZr9N2KzVJWC8eNphZVuYkBay9tHp6qC6BMyN5Pr1YGnWDNMX8ivyrogza6wiJga8rvBSN2brt6tU5pWHpkBRRZYySTP69G5utxvkLKuk26xvvMuXJbW5TuTttKEDCLewsejh5yyijfiEkkXxNd6jWPUpVTKMespJ2pusyWH5ZqD8CVJPrPMpEEnFrgRwjRyGdwu9uvkKvUuLBRNMPAc7G4JWqsiqXvkjRj7WLDvjHZ3NEkD26xyT3nAT9ZnwEth4BvxMYE6EGoD9adNBqm8XzQ2heWNjpf9n56vjaNuSmLUwpwMr3XLwMMrggwhNUt7y8aYoZTYsbiRL4R4YhATwvwmikNbgWpuk1ckun66G88dyjmUGkpqME5Qd35AH1A1YV1X2cdnQEFwToo21A8e2A7x28qiugP4Y4fJSo51FxsAJL71VCRxExbWJKm512TF4ATDkrb5uqLrmhojeGjxzbHmb5SHBAPDnjEc6fJ7qNYXvMNqgV4vDkdcbJeuF7cmEs8sovqLx6eSAjEv1wUJJTTsLmPZZ7MhJe8FRH3f3aRT6ZYwMGY71Ga6ZHAWXcGYnmjYmqgh8sdN8bFS9Dxr6ANA8KjEUREnan4MX3eC1Yo2rQpTuG6AZYb3PfNdrkw5xdiXRyGpZJScpHhxhRWBCBP4nVk9qRuLs8VHXd7h388Q1JofAqXRoJmRWyeX6NWCmdS6QAq4HzYV7nVdrybPMrFS88tdgqhoseqrgnS1DZ",
"assets": [
{
"tokenId": "6f1a7c49a4e8cab3e877a46bf4ef7beb5ba1df4ece92c40cd0770b07ccb369ae",
"index": 0,
"amount": 1,
"name": "Sigmanauts Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00b6f6e34943cef98f5302c54cf13a81f7ab5cd6af2d7b14cf51d835e4e8288c",
"index": 1,
"amount": 35,
"name": "Sigmanaut",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107bcb9a8879164444200000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1720276291166,34,33,0,0,0,0]"
},
"R6": {
"serializedValue": "1d05023e44020c30020c30023232023232",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[31,34],[6,24],[6,24],[25,25],[25,25]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c646402f149b169414a345b35bfe8cafb1423bb1a90a7bc9cef7935ac1a5d36b7d9ead3060720000f55a1605b158c40187671d5d10a41257521b53bee69b7cb8ebb26d9caa901ff03072000cbf4cf467af6108dcbd5ad75015ee7ea704b15d03057bbc11b564e631c97608c060720001ed37cbfcd036f7d503fd9cbfefc42b43f9267133cb263e2083d6a91e63d5cbe05072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c6402cbf4cf467af6108dcbd5ad75015ee7ea704b15d03057bbc11b564e631c97608c060720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "cf9829f4c584600136c7226cd286b8f3688a11c5af2b3a93362401200cee37ab",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "0584c35e7372878927231fd41d22dc9c2d1cd978a761e1fc3691fee9240de6f4",
"outputTransactionId": "954294bea4cd8983c91bbddd6d1808c0aa31610e98a2f02afbb7f4d2a6f012b4",
"outputIndex": 1,
"outputGlobalIndex": 40857778,
"outputCreatedAt": 1287885,
"outputSettledAt": 1287887,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-17,-60,-10,3,-34,-90,4,18,-122,-88,-97,91,-43,22,-84,-106,-22,91,37,-38,79,8,-41,108,105,39,-32,29,97,-78,42,-33)\n3: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n4: Coll(73,50,-62,-121,84,-14,-28,-6,-72,-24,90,-8,-18,61,-21,91,-66,73,36,-73,88,84,102,-46,13,-18,-44,-55,-98,65,-111,-94)\n5: 0\n6: 2\n7: 0\n8: 6\n9: 37\n10: 5\n11: 6\n12: 37\n13: 5\n14: 6\n15: 37\n16: 1\n17: 4\n18: 0\n19: 8\n20: 8\n21: 8\n22: -1\n23: 0\n24: 8\n25: 16\n26: 0\n27: 0\n28: 1\n29: 0\n30: 3\n31: 0\n32: 0\n33: 0\n34: 2\n35: 0\n36: 4\n37: 0\n38: 0\n39: 0\n40: 0\n41: 100\n42: 0\n43: 100\n44: CBigInt(0)\n45: CBigInt(0)\n46: 0\n47: 8\n48: 8\n49: 16\n50: 0\n51: 0\n52: 8\n53: 8\n54: 8\n55: CBigInt(0)\n56: true\n57: 0\n58: 0\n59: 0\n60: 0\n61: 0\n62: 0\n63: CBigInt(0)\n64: 0\n65: 0\n66: 1\n67: 1\n68: 1\n69: 0\n70: Coll(56,-68,56,81,78,28,46,-125,35,35,15,64,-22,39,-43,43,-118,-49,66,82,8,-17,-118,10,-96,-7,-25,75,-28,27,28,-124)\n71: 0\n72: 0\n73: 6\n74: 38\n75: 0\n76: 0\n77: 0\n78: 0\n79: 0\n80: 0\n81: 1\n82: 0\n83: 1\n84: 8\n85: 16\n86: 0\n87: 0\n88: 1\n89: 1\n90: 33\n91: 1\n92: 1\n93: 0\n94: 0\n95: 2\n96: 5\n97: 2\n98: 5\n99: 10\n100: 78\n101: -58\n102: 31\n103: 72\n104: 91\n105: -104\n106: -21\n107: -121\n108: 21\n109: 63\n110: 124\n111: 87\n112: -37\n113: 79\n114: 94\n115: -51\n116: 117\n117: 85\n118: 111\n119: -35\n120: -68\n121: 64\n122: 59\n123: 65\n124: -84\n125: -8\n126: 68\n127: 31\n128: -34\n129: -114\n130: 22\n131: 9\n132: 0\n133: 5",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val box2 = INPUTS(placeholder[Int](1))\n val coll3 = box2.tokens\n val coll4 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4)), getVar[Coll[Byte]](0.toByte).get\n )\n val coll5 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val coll6 = coll5.map({(tuple6: (Coll[Byte], Coll[Byte])) => tuple6._1 })\n val coll7 = coll6.indices\n val coll8 = box2.R4[Coll[AvlTree]].get\n val avlTree9 = coll8(placeholder[Int](5))\n val coll10 = box2.R5[Coll[Long]].get\n val i11 = coll10.size\n val coll12 = coll4(placeholder[Int](6)).get\n val coll13 = coll12.slice(placeholder[Int](7), coll12.size - placeholder[Int](8) / placeholder[Int](9)).indices\n val coll14 = coll10.slice(placeholder[Int](10), i11).append(\n coll13.map(\n {(i14: Int) =>\n coll12.slice(\n placeholder[Int](11) + placeholder[Int](12) * i14 + placeholder[Int](13), placeholder[Int](14) + placeholder[Int](15) * i14 + placeholder[Int](16)\n )\n }\n ).slice(i11 - placeholder[Int](17), coll13.size).map({(coll14: Coll[Byte]) => placeholder[Long](18) })\n )\n val coll15 = coll14.indices\n val coll16 = avlTree9.getMany(coll6, getVar[Coll[Byte]](2.toByte).get).map({(opt16: Option[Coll[Byte]]) => if (opt16.isDefined) { coll15.map({(i18: Int) =>\n val i20 = i18 * placeholder[Int](19) + placeholder[Int](20)\n byteArrayToLong(opt16.get.slice(i20, i20 + placeholder[Int](21)))\n }) } else { coll14.map({(l18: Long) => placeholder[Long](22) }) } })\n val coll17 = box2.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple18 = coll17(placeholder[Int](23))\n val avlTree19 = tuple18._1\n val coll20 = avlTree19.getMany(coll6, getVar[Coll[Byte]](3.toByte).get).map(\n {(opt20: Option[Coll[Byte]]) => byteArrayToLong(opt20.get.slice(placeholder[Int](24), placeholder[Int](25))) }\n )\n val coll21 = box2.R6[Coll[Coll[Long]]].get\n val l22 = coll21(placeholder[Int](26))(placeholder[Int](27))\n val l23 = coll21(placeholder[Int](28))(placeholder[Int](29))\n val coll24 = coll21(placeholder[Int](30))\n val b25 = if (l23 > placeholder[Long](31)) { coll24(placeholder[Int](32)).toByte } else { placeholder[Byte](33) }\n val l26 = coll21(placeholder[Int](34))(placeholder[Int](35))\n val coll27 = coll21(placeholder[Int](36))\n val b28 = if (l26 > placeholder[Long](37)) { coll27(placeholder[Int](38)).toByte } else { placeholder[Byte](39) }\n val b29 = b25 + b28\n val b30 = if (b29.toInt > placeholder[Int](40)) { max(placeholder[Byte](41) - b29, placeholder[Byte](42)) } else { placeholder[Byte](43) }\n val bi31 = placeholder[BigInt](44)\n val bi32 = placeholder[BigInt](45)\n val b33 = b29 + b30\n val avlTree34 = tuple18._2\n val coll35 = avlTree34.getMany(coll6, getVar[Coll[Byte]](5.toByte).get).map({(opt35: Option[Coll[Byte]]) => if (opt35.isDefined) {(\n val coll37 = opt35.get\n (byteArrayToLong(coll37.slice(placeholder[Int](46), placeholder[Int](47))), byteArrayToLong(coll37.slice(placeholder[Int](48), placeholder[Int](49))))\n )} else { (placeholder[Long](50), placeholder[Long](51)) } })\n val coll36 = box2.R8[Coll[Long]].get\n val coll37 = coll5.map({(tuple37: (Coll[Byte], Coll[Byte])) => coll15.map({(i39: Int) =>\n val i41 = i39 * placeholder[Int](52) + placeholder[Int](53)\n byteArrayToLong(tuple37._2.slice(i41, i41 + placeholder[Int](54)))\n }) })\n val tuple38 = (coll36.map({(l38: Long) => placeholder[BigInt](55) }), placeholder[Boolean](56))\n val coll39 = coll36.indices.map({(i39: Int) => coll7.map({(i41: Int) =>\n val coll43 = coll16(i41)\n if (coll43(placeholder[Int](57)) >= placeholder[Long](58)) {(\n val coll44 = coll36.map({(l44: Long) =>\n val bi46 = l44.toBigInt\n coll20(i41).toBigInt * bi46 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](59)) { coll35(i41)._1.toBigInt * bi46 / l23.toBigInt * coll24(placeholder[Int](60)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](61)) { coll35(i41)._2.toBigInt * bi46 / l26.toBigInt * coll27(placeholder[Int](62)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll44, coll43.zip(coll44).map({(tuple45: (Long, BigInt)) => tuple45._1.toBigInt + tuple45._2 }) == coll37(i41).map({(l45: Long) => l45.toBigInt }))\n )} else { tuple38 }\n }).fold(placeholder[BigInt](63), {(tuple41: (BigInt, (Coll[BigInt], Boolean))) => tuple41._1 + tuple41._2._1(i39) }) })\n val box40 = OUTPUTS(placeholder[Int](64))\n val coll41 = box40.R5[Coll[Long]].get\n val coll42 = box40.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple43 = coll42(placeholder[Int](65))\n val coll44 = tuple43._1.digest\n val coll45 = box40.R4[Coll[AvlTree]].get\n val box46 = OUTPUTS(placeholder[Int](66))\n val bool47 = tuple43._2 == avlTree34\n val bool48 = coll42.slice(placeholder[Int](67), coll42.size) == coll17.slice(placeholder[Int](68), coll17.size)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](69))._1 == placeholder[Coll[Byte]](70), coll3(placeholder[Int](71))._1 == coll4(placeholder[Int](72)).get.slice(\n placeholder[Int](73), placeholder[Int](74)\n ), allOf(coll7.map({(i49: Int) =>\n val coll51 = coll16(i49)\n if (coll51(placeholder[Int](75)) >= placeholder[Long](76)) {(\n val coll52 = coll36.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll20(i49).toBigInt * bi54 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](77)) { coll35(i49)._1.toBigInt * bi54 / l23.toBigInt * coll24(placeholder[Int](78)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](79)) { coll35(i49)._2.toBigInt * bi54 / l26.toBigInt * coll27(placeholder[Int](80)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll37(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple38 }._2\n })), coll10(placeholder[Int](81)).toBigInt + coll39(placeholder[Int](82)) == coll41(placeholder[Int](83)).toBigInt, avlTree19.remove(\n coll6, getVar[Coll[Byte]](4.toByte).get\n ).get.digest == coll44, avlTree9.update(\n coll5.filter(\n {(tuple49: (Coll[Byte], Coll[Byte])) => byteArrayToLong(tuple49._2.slice(placeholder[Int](84), placeholder[Int](85))) > placeholder[Long](86) }\n ), getVar[Coll[Byte]](6.toByte).get\n ).get.digest == coll45(placeholder[Int](87)).digest, allOf(\n Coll[Boolean](\n blake2b256(box46.propositionBytes) == coll4(placeholder[Int](88)).get.slice(placeholder[Int](89), placeholder[Int](90)), box46.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n box40.value == box2.value, box40.tokens == coll3, coll45(placeholder[Int](91)).digest == coll8(placeholder[Int](92)).digest, bool47, bool48, coll41(\n placeholder[Int](93)\n ) == coll10(placeholder[Int](94)), coll41.slice(placeholder[Int](95), placeholder[Int](96)) == coll10.slice(\n placeholder[Int](97), placeholder[Int](98)\n ), box40.R6[Coll[Coll[Long]]].get == coll21, bool48, bool47, box40.R8[Coll[Long]].get == coll36\n )\n ), (coll5.size >= placeholder[Int](99)) || (\n coll44 == Coll[Byte](\n placeholder[Byte](100), placeholder[Byte](101), placeholder[Byte](102), placeholder[Byte](103), placeholder[Byte](104), placeholder[Byte](\n 105\n ), placeholder[Byte](106), placeholder[Byte](107), placeholder[Byte](108), placeholder[Byte](109), placeholder[Byte](110), placeholder[Byte](\n 111\n ), placeholder[Byte](112), placeholder[Byte](113), placeholder[Byte](114), placeholder[Byte](115), placeholder[Byte](116), placeholder[Byte](\n 117\n ), placeholder[Byte](118), placeholder[Byte](119), placeholder[Byte](120), placeholder[Byte](121), placeholder[Byte](122), placeholder[Byte](\n 123\n ), placeholder[Byte](124), placeholder[Byte](125), placeholder[Byte](126), placeholder[Byte](127), placeholder[Byte](128), placeholder[Byte](\n 129\n ), placeholder[Byte](130), placeholder[Byte](131), placeholder[Byte](132)\n )\n ), coll15.forall({(i49: Int) => coll41.slice(placeholder[Int](133), coll41.size)(i49).toBigInt == coll14(i49).toBigInt - coll39(i49) })\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "b5d66446fc3c04efebc1b7536d6ac18e34a3710d1eec03d7f594b29fabba0880",
"value": 50214000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "ebb325effd7cfb17bbea9ba798a2a17755f1e7499f3f652ee981110987e89fd7",
"outputTransactionId": "d4b2fcfb3bae6a74ce884837611fc55f255b411dcfdd36b5e900433cca42399f",
"outputIndex": 5,
"outputGlobalIndex": 41072596,
"outputCreatedAt": 1295018,
"outputSettledAt": 1295020,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(91,-117,93,112,-70,-63,71,-15,-126,-107,12,-61,82,-95,-86,-66,121,-55,-61,-90,101,0,-87,104,76,30,-15,-126,-3,-73,71,63)\n3: false\n4: Coll(0,64,-82,101,12,78,-41,123,-51,32,57,20,-109,-85,-24,76,26,-101,-75,-114,-24,-114,-121,-15,86,112,-56,1,-30,-4,89,-125)\n5: Coll(91,-49,-15,2,37,67,102,120,12,-43,25,18,87,5,10,110,-45,58,-59,-47,46,-17,14,48,65,57,-19,93,-104,31,75,-6)\n6: 0\n7: 0\n8: 0\n9: 1\n10: 0\n11: 0\n12: 0\n13: 0\n14: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n15: Coll(79,-40,-80,-42,-39,-126,66,114,111,87,-77,-33,-90,-122,18,103,-110,-72,-27,5,110,29,81,-74,-23,13,104,-128,-49,45,-51,-59)\n16: 0\n17: 0\n18: Coll(34,94,63,-59,-47,-119,-11,71,-39,-58,38,-66,-67,-58,113,57,-117,108,0,124,120,61,-60,127,-112,63,36,-65,127,52,-124,121)\n19: Coll(-68,74,90,-71,-28,90,-73,75,121,-6,-20,-65,103,73,108,-62,-65,-116,43,14,85,-37,-24,-84,-49,-61,-99,20,-119,17,116,-112)\n20: Coll(118,124,-86,-128,-71,-114,73,106,-40,-87,-10,-119,-60,65,10,-28,83,50,127,15,-107,-23,80,-124,-64,-82,32,99,80,121,59,119)\n21: 0\n22: 1\n23: 9\n24: 2\n25: 1\n26: 2\n27: 1\n28: 33\n29: 0\n30: 0\n31: 3\n32: 1\n33: 9\n34: 0\n35: 0\n36: 1\n37: 1\n38: 9\n39: 1\n40: 1\n41: 1\n42: 33\n43: Coll(-20,-14,-48,75,-82,72,-96,10,-118,110,73,-64,86,114,99,-55,-11,-46,63,38,-56,35,88,-95,118,-85,-47,-16,33,-40,-79,48)\n44: 1\n45: 1\n46: 9\n47: 0\n48: 0\n49: 0\n50: 1\n51: 9\n52: 1\n53: 0\n54: 1\n55: 33\n56: 1\n57: 1\n58: false",
"ergoTreeScript": "{\n val bool1 = INPUTS.exists({(box1: Box) =>\n val coll3 = box1.tokens\n if (coll3.size > placeholder[Int](0)) { coll3(placeholder[Int](1))._1 == placeholder[Coll[Byte]](2) } else { placeholder[Boolean](3) }\n })\n val coll2 = placeholder[Coll[Byte]](4)\n val coll3 = placeholder[Coll[Byte]](5)\n sigmaProp(anyOf(Coll[Boolean](bool1, if (!bool1) {(\n val box4 = OUTPUTS(placeholder[Int](6))\n val coll5 = box4.R5[Coll[Long]].get\n val box6 = INPUTS(placeholder[Int](7))\n val coll7 = SELF.propositionBytes\n val box8 = OUTPUTS.filter({(box8: Box) => box8.propositionBytes == coll7 })(placeholder[Int](8))\n val coll9 = CONTEXT.dataInputs\n val avlTree10 = coll9(placeholder[Int](9)).R4[AvlTree].get\n val coll11 = getVar[Coll[Byte]](0.toByte).get\n val coll12 = INPUTS.filter({(box12: Box) => box12.propositionBytes == coll7 })\n val l13 = coll12.fold(placeholder[Long](10), {(tuple13: (Long, Box)) => tuple13._1 + tuple13._2.value })\n val coll14 = box8.tokens\n val func15 = {(coll15: Coll[Byte]) => coll12.flatMap({(box17: Box) => box17.tokens }).fold(placeholder[Long](11), {(tuple17: (Long, (Coll[Byte], Long))) =>\n val tuple19 = tuple17._2\n tuple17._1 + if (tuple19._1 == coll15) { tuple19._2 } else { placeholder[Long](12) }\n }) }\n val l16 = func15(coll2)\n val coll17 = coll9(placeholder[Int](13)).R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](14), placeholder[Coll[Byte]](15)), getVar[Coll[Byte]](1.toByte).get)\n val bool18 = coll14.filter({(tuple18: (Coll[Byte], Long)) => tuple18._1 != coll2 }).forall({(tuple18: (Coll[Byte], Long)) => tuple18._2 == func15(tuple18._1) })\n val bool19 = coll12.flatMap({(box19: Box) => box19.tokens }).forall({(tuple19: (Coll[Byte], Long)) =>\n val coll21 = tuple19._1\n (coll21 == coll2) || box8.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 })\n })\n if (coll5(placeholder[Int](16)) > box6.R5[Coll[Long]].get(placeholder[Int](17))) {(\n val coll20 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](18), placeholder[Coll[Byte]](19), placeholder[Coll[Byte]](20), coll3), coll11)\n val l21 = byteArrayToLong(coll20(placeholder[Int](21)).get.slice(placeholder[Int](22), placeholder[Int](23))) * coll5(placeholder[Int](24)) + placeholder[Long](25)\n val tuple22 = OUTPUTS.filter({(box22: Box) => blake2b256(box22.propositionBytes) == coll20(placeholder[Int](26)).get.slice(placeholder[Int](27), placeholder[Int](28)) })(placeholder[Int](29)).tokens(placeholder[Int](30))\n allOf(Coll[Boolean](box8.value >= l13 - byteArrayToLong(coll20(placeholder[Int](31)).get.slice(placeholder[Int](32), placeholder[Int](33))), coll14.fold(placeholder[Long](34), {(tuple23: (Long, (Coll[Byte], Long))) =>\n val tuple25 = tuple23._2\n tuple23._1 + if (tuple25._1 == coll2) { tuple25._2 } else { placeholder[Long](35) }\n }) >= l16 - l21 - byteArrayToLong(coll20(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38))), bool18, bool19, tuple22._1 == coll2, tuple22._2 >= l21, blake2b256(INPUTS(placeholder[Int](39)).propositionBytes) == coll17(placeholder[Int](40)).get.slice(placeholder[Int](41), placeholder[Int](42))))\n )} else {(\n val coll20 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](43), coll3), coll11)\n allOf(Coll[Boolean](box8.value >= l13 - byteArrayToLong(coll20(placeholder[Int](44)).get.slice(placeholder[Int](45), placeholder[Int](46))), coll14.fold(placeholder[Long](47), {(tuple21: (Long, (Coll[Byte], Long))) =>\n val tuple23 = tuple21._2\n tuple21._1 + if (tuple23._1 == coll2) { tuple23._2 } else { placeholder[Long](48) }\n }) >= l16 - byteArrayToLong(coll20(placeholder[Int](49)).get.slice(placeholder[Int](50), placeholder[Int](51))), bool18, bool19, blake2b256(INPUTS(placeholder[Int](52)).propositionBytes) == coll17(placeholder[Int](53)).get.slice(placeholder[Int](54), placeholder[Int](55)), box4.tokens(placeholder[Int](56))._2 == box6.tokens(placeholder[Int](57))._2))\n )}\n )} else { placeholder[Boolean](58) })))\n}",
"address": "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",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 1071511683,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "00b6f6e34943cef98f5302c54cf13a81f7ab5cd6af2d7b14cf51d835e4e8288c",
"index": 1,
"amount": 99948,
"name": "Sigmanaut",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "6b0b12bf7250b9665959194961f89327b56dd8fb44436c0a70ca0bf0bae0f50f",
"value": 1000000,
"index": 0,
"outputBlockId": "9175984dfa2ac2b7f35c1d6f8f3b66e6d46a609acd82ca9e9b01d82590e9680c",
"outputTransactionId": "827d951edfdc547162709b7dcdd2f9580a9903df95b59806e081aad2fe369cf0",
"outputIndex": 1,
"ergoTree": "100904000e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020442040004000e205b8b5d70bac147f182950cc352a1aabe79c9c3a66500a9684c1ef182fdb7473f0100d801d601b2a5730000d19683040193db6308a7db6308720190c1a7c1720193cbc27201b4e4b2dc640be4c6720104640283010e7301e4e3000e73020073037304aea4d9010263d801d604db630872029591b172047305938cb272047306000173077308",
"address": "FDdVv3XcPnh67Hm9GfPJpFCLuVeaYKY9MGf67RZfgNcGhsxDZPTz5JVn86hKGoSf3aCbfjFnGQtD8YobxJEaqgNzhHkXs7cJLF4fpeG9Rc7e7MhMxf2heSgkXQZo6HXoH9e9V8dPLHnnuBtS4cdn4hm8o6m1ZTJkNea4S7ge2EAn3mVRfGTRehPjp2HWqX613K1LMRmB3k1skpk3X388c6aAcNSxwhtbMbeoCqAA6HP7U2gyANsbdAyp8y56yQqP",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "6445d8740d3e0927df4e5d0be8cbf74f01c517dbc91256de18e375c1345f79c81f06072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "7a017d90be6f916a98137a8129b1cc1b278f581a49930f5b2e127656a39dad1c",
"value": 1000000,
"index": 1,
"outputBlockId": "60de8f3da68eef2d0ea14ba2d51880b8dab2bf68f7681ff99623a49e66c49032",
"outputTransactionId": "4834902bf55d99b44ce916c6ea831cb9f32bf3e6a764739c6ef6522c195dfc76",
"outputIndex": 0,
"ergoTree": "100904000e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020442040004000e20008a3b597bd494557adf7d0d0a3b6ba32f935cf52f83f46a6b1233333a487a510100d801d601b2a5730000d19683040193db6308a7db6308720190c1a7c1720193cbc27201b4e4b2dc640be4c6720104640283010e7301e4e3000e73020073037304aea4d9010263d801d604db630872029591b172047305938cb272047306000173077308",
"address": "FDdVv3XcPnh67Hm9GfPJpFCLuVeaYKY9MGf67RZfgNcGhsxDZPTz5JVn86hKGoSf3aCbfCuknDpV3PzizoM2efhYNFH3o7uHxSjqDTXCRdcV2F4vMAbtG8fxGWK9ZxWniTZ6GFE5mT7DEpU6W6piUfh32UkeqxrkxS1Gb6KitQDAbSnrTwCceBFbSkmGRLmPxi26PrzREXVVz4UnXjm1xmFrng6vu6NtPvPfEzz1a4asj856HV8Pq1mMx3UgNfeA",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64e9b1559d094874384dd067d9dbef01de6a53fe1525ef27657b627e2af8d08cf908072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "b1cfca27b2ef08a5761d7400231503fdae233761f0dd89b9f65929412907f84d",
"transactionId": "387bd2db14877e281e08c9ee475fdd0b48b4df56d366d575c486822689e35f24",
"blockId": "ebb325effd7cfb17bbea9ba798a2a17755f1e7499f3f652ee981110987e89fd7",
"value": 1000000,
"index": 0,
"globalIndex": 41072597,
"creationHeight": 1295018,
"settlementHeight": 1295020,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: Coll(-34,-82,-49,91,100,-70,-42,-11,87,11,-83,10,97,12,78,72,73,87,-49,71,-126,48,-124,0,-68,-112,64,76,29,20,16,-38)\n3: Coll(3,-110,8,-68,78,-17,-102,3,-24,-41,-117,-122,99,-93,1,-69,95,-83,-36,-89,-117,-31,-99,127,-27,53,-77,-58,76,-66,-2,66)\n4: Coll(-120,48,97,44,82,53,95,111,40,13,18,-105,-15,-97,103,-80,120,-55,-38,-89,-41,-80,75,69,-100,-111,-52,100,73,87,-62,-128)\n5: Coll(-117,-57,-113,28,106,-82,-55,30,98,-114,21,-49,102,-116,22,-52,30,-101,-40,-28,-71,-73,-31,109,99,24,-75,-11,35,-91,-23,-67)\n6: Coll(79,-40,-80,-42,-39,-126,66,114,111,87,-77,-33,-90,-122,18,103,-110,-72,-27,5,110,29,81,-74,-23,13,104,-128,-49,45,-51,-59)\n7: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n8: Coll(58,17,-107,92,71,25,-27,-120,-68,-26,-89,97,29,39,-67,31,-33,-37,87,56,92,-82,-30,102,-40,4,12,-119,79,28,46,29)\n9: Coll(9,-126,15,-53,-120,113,-5,69,12,62,6,-73,-53,94,39,-80,69,80,-121,-93,102,98,26,-99,-34,117,-126,-96,25,17,30,62)\n10: 0\n11: 0\n12: Coll(56,-68,56,81,78,28,46,-125,35,35,15,64,-22,39,-43,43,-118,-49,66,82,8,-17,-118,10,-96,-7,-25,75,-28,27,28,-124)\n13: 0\n14: 6\n15: 0\n16: 1\n17: 1\n18: 33\n19: 1\n20: 2\n21: 1\n22: 33\n23: 2\n24: 3\n25: 1\n26: 33\n27: 3\n28: 4\n29: 1\n30: 33\n31: 4\n32: 5\n33: 1\n34: 33\n35: 5\n36: 6\n37: 1\n38: 33\n39: 6\n40: 7\n41: 1\n42: 33\n43: 0\n44: 1\n45: 33\n46: 0\n47: 0\n48: 1\n49: 1",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val b2 = getVar[Byte](1.toByte).get\n val i3 = b2.toInt\n val box4 = INPUTS(placeholder[Int](1))\n val coll5 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](\n placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4), placeholder[Coll[Byte]](5), placeholder[Coll[Byte]](6), placeholder[\n Coll[Byte]\n ](7), placeholder[Coll[Byte]](8), placeholder[Coll[Byte]](9)\n ), getVar[Coll[Byte]](0.toByte).get\n )\n val box6 = OUTPUTS(placeholder[Int](10))\n val coll7 = box6.tokens\n val coll8 = SELF.tokens\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), (i3 >= placeholder[Int](13)) && (i3 <= placeholder[Int](14)), anyOf(\n Coll[Boolean](\n (b2 == placeholder[Byte](15)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](16)).get.slice(placeholder[Int](17), placeholder[Int](18))\n ), (b2 == placeholder[Byte](19)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](20)).get.slice(placeholder[Int](21), placeholder[Int](22))\n ), (b2 == placeholder[Byte](23)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](24)).get.slice(placeholder[Int](25), placeholder[Int](26))\n ), (b2 == placeholder[Byte](27)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](28)).get.slice(placeholder[Int](29), placeholder[Int](30))\n ), (b2 == placeholder[Byte](31)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](32)).get.slice(placeholder[Int](33), placeholder[Int](34))\n ), (b2 == placeholder[Byte](35)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38))\n ), (b2 == placeholder[Byte](39)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](40)).get.slice(placeholder[Int](41), placeholder[Int](42))\n )\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box6.propositionBytes) == coll5(placeholder[Int](43)).get.slice(placeholder[Int](44), placeholder[Int](45)), coll7(\n placeholder[Int](46)\n ) == coll8(placeholder[Int](47)), coll7(placeholder[Int](48))._1 == coll8(placeholder[Int](49))._1\n )\n )\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "6f1a7c49a4e8cab3e877a46bf4ef7beb5ba1df4ece92c40cd0770b07ccb369ae",
"index": 0,
"amount": 1,
"name": "Sigmanauts Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00b6f6e34943cef98f5302c54cf13a81f7ab5cd6af2d7b14cf51d835e4e8288c",
"index": 1,
"amount": 35,
"name": "Sigmanaut",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107bcb9a8879164444200000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1720276291166,34,33,0,0,0,0]"
},
"R6": {
"serializedValue": "1d05023e44020c30020c30023232023232",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[31,34],[6,24],[6,24],[25,25],[25,25]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464024ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720000f55a1605b158c40187671d5d10a41257521b53bee69b7cb8ebb26d9caa901ff03072000cbf4cf467af6108dcbd5ad75015ee7ea704b15d03057bbc11b564e631c97608c060720001ed37cbfcd036f7d503fd9cbfefc42b43f9267133cb263e2083d6a91e63d5cbe05072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c6402cbf4cf467af6108dcbd5ad75015ee7ea704b15d03057bbc11b564e631c97608c060720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "04477f876e1989fc7a4425304e6d6ac3e90718f3f17706c71a7fa466218ecf48",
"mainChain": true
},
{
"boxId": "8bf0bc984946e4e043a4d90c80c57f9d96c1ae5e1b8771f3990e3ce2be38b36f",
"transactionId": "387bd2db14877e281e08c9ee475fdd0b48b4df56d366d575c486822689e35f24",
"blockId": "ebb325effd7cfb17bbea9ba798a2a17755f1e7499f3f652ee981110987e89fd7",
"value": 1000000,
"index": 1,
"globalIndex": 41072598,
"creationHeight": 1295018,
"settlementHeight": 1295020,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-17,-60,-10,3,-34,-90,4,18,-122,-88,-97,91,-43,22,-84,-106,-22,91,37,-38,79,8,-41,108,105,39,-32,29,97,-78,42,-33)\n3: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n4: Coll(73,50,-62,-121,84,-14,-28,-6,-72,-24,90,-8,-18,61,-21,91,-66,73,36,-73,88,84,102,-46,13,-18,-44,-55,-98,65,-111,-94)\n5: 0\n6: 2\n7: 0\n8: 6\n9: 37\n10: 5\n11: 6\n12: 37\n13: 5\n14: 6\n15: 37\n16: 1\n17: 4\n18: 0\n19: 8\n20: 8\n21: 8\n22: -1\n23: 0\n24: 8\n25: 16\n26: 0\n27: 0\n28: 1\n29: 0\n30: 3\n31: 0\n32: 0\n33: 0\n34: 2\n35: 0\n36: 4\n37: 0\n38: 0\n39: 0\n40: 0\n41: 100\n42: 0\n43: 100\n44: CBigInt(0)\n45: CBigInt(0)\n46: 0\n47: 8\n48: 8\n49: 16\n50: 0\n51: 0\n52: 8\n53: 8\n54: 8\n55: CBigInt(0)\n56: true\n57: 0\n58: 0\n59: 0\n60: 0\n61: 0\n62: 0\n63: CBigInt(0)\n64: 0\n65: 0\n66: 1\n67: 1\n68: 1\n69: 0\n70: Coll(56,-68,56,81,78,28,46,-125,35,35,15,64,-22,39,-43,43,-118,-49,66,82,8,-17,-118,10,-96,-7,-25,75,-28,27,28,-124)\n71: 0\n72: 0\n73: 6\n74: 38\n75: 0\n76: 0\n77: 0\n78: 0\n79: 0\n80: 0\n81: 1\n82: 0\n83: 1\n84: 8\n85: 16\n86: 0\n87: 0\n88: 1\n89: 1\n90: 33\n91: 1\n92: 1\n93: 0\n94: 0\n95: 2\n96: 5\n97: 2\n98: 5\n99: 10\n100: 78\n101: -58\n102: 31\n103: 72\n104: 91\n105: -104\n106: -21\n107: -121\n108: 21\n109: 63\n110: 124\n111: 87\n112: -37\n113: 79\n114: 94\n115: -51\n116: 117\n117: 85\n118: 111\n119: -35\n120: -68\n121: 64\n122: 59\n123: 65\n124: -84\n125: -8\n126: 68\n127: 31\n128: -34\n129: -114\n130: 22\n131: 9\n132: 0\n133: 5",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val box2 = INPUTS(placeholder[Int](1))\n val coll3 = box2.tokens\n val coll4 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4)), getVar[Coll[Byte]](0.toByte).get\n )\n val coll5 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val coll6 = coll5.map({(tuple6: (Coll[Byte], Coll[Byte])) => tuple6._1 })\n val coll7 = coll6.indices\n val coll8 = box2.R4[Coll[AvlTree]].get\n val avlTree9 = coll8(placeholder[Int](5))\n val coll10 = box2.R5[Coll[Long]].get\n val i11 = coll10.size\n val coll12 = coll4(placeholder[Int](6)).get\n val coll13 = coll12.slice(placeholder[Int](7), coll12.size - placeholder[Int](8) / placeholder[Int](9)).indices\n val coll14 = coll10.slice(placeholder[Int](10), i11).append(\n coll13.map(\n {(i14: Int) =>\n coll12.slice(\n placeholder[Int](11) + placeholder[Int](12) * i14 + placeholder[Int](13), placeholder[Int](14) + placeholder[Int](15) * i14 + placeholder[Int](16)\n )\n }\n ).slice(i11 - placeholder[Int](17), coll13.size).map({(coll14: Coll[Byte]) => placeholder[Long](18) })\n )\n val coll15 = coll14.indices\n val coll16 = avlTree9.getMany(coll6, getVar[Coll[Byte]](2.toByte).get).map({(opt16: Option[Coll[Byte]]) => if (opt16.isDefined) { coll15.map({(i18: Int) =>\n val i20 = i18 * placeholder[Int](19) + placeholder[Int](20)\n byteArrayToLong(opt16.get.slice(i20, i20 + placeholder[Int](21)))\n }) } else { coll14.map({(l18: Long) => placeholder[Long](22) }) } })\n val coll17 = box2.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple18 = coll17(placeholder[Int](23))\n val avlTree19 = tuple18._1\n val coll20 = avlTree19.getMany(coll6, getVar[Coll[Byte]](3.toByte).get).map(\n {(opt20: Option[Coll[Byte]]) => byteArrayToLong(opt20.get.slice(placeholder[Int](24), placeholder[Int](25))) }\n )\n val coll21 = box2.R6[Coll[Coll[Long]]].get\n val l22 = coll21(placeholder[Int](26))(placeholder[Int](27))\n val l23 = coll21(placeholder[Int](28))(placeholder[Int](29))\n val coll24 = coll21(placeholder[Int](30))\n val b25 = if (l23 > placeholder[Long](31)) { coll24(placeholder[Int](32)).toByte } else { placeholder[Byte](33) }\n val l26 = coll21(placeholder[Int](34))(placeholder[Int](35))\n val coll27 = coll21(placeholder[Int](36))\n val b28 = if (l26 > placeholder[Long](37)) { coll27(placeholder[Int](38)).toByte } else { placeholder[Byte](39) }\n val b29 = b25 + b28\n val b30 = if (b29.toInt > placeholder[Int](40)) { max(placeholder[Byte](41) - b29, placeholder[Byte](42)) } else { placeholder[Byte](43) }\n val bi31 = placeholder[BigInt](44)\n val bi32 = placeholder[BigInt](45)\n val b33 = b29 + b30\n val avlTree34 = tuple18._2\n val coll35 = avlTree34.getMany(coll6, getVar[Coll[Byte]](5.toByte).get).map({(opt35: Option[Coll[Byte]]) => if (opt35.isDefined) {(\n val coll37 = opt35.get\n (byteArrayToLong(coll37.slice(placeholder[Int](46), placeholder[Int](47))), byteArrayToLong(coll37.slice(placeholder[Int](48), placeholder[Int](49))))\n )} else { (placeholder[Long](50), placeholder[Long](51)) } })\n val coll36 = box2.R8[Coll[Long]].get\n val coll37 = coll5.map({(tuple37: (Coll[Byte], Coll[Byte])) => coll15.map({(i39: Int) =>\n val i41 = i39 * placeholder[Int](52) + placeholder[Int](53)\n byteArrayToLong(tuple37._2.slice(i41, i41 + placeholder[Int](54)))\n }) })\n val tuple38 = (coll36.map({(l38: Long) => placeholder[BigInt](55) }), placeholder[Boolean](56))\n val coll39 = coll36.indices.map({(i39: Int) => coll7.map({(i41: Int) =>\n val coll43 = coll16(i41)\n if (coll43(placeholder[Int](57)) >= placeholder[Long](58)) {(\n val coll44 = coll36.map({(l44: Long) =>\n val bi46 = l44.toBigInt\n coll20(i41).toBigInt * bi46 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](59)) { coll35(i41)._1.toBigInt * bi46 / l23.toBigInt * coll24(placeholder[Int](60)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](61)) { coll35(i41)._2.toBigInt * bi46 / l26.toBigInt * coll27(placeholder[Int](62)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll44, coll43.zip(coll44).map({(tuple45: (Long, BigInt)) => tuple45._1.toBigInt + tuple45._2 }) == coll37(i41).map({(l45: Long) => l45.toBigInt }))\n )} else { tuple38 }\n }).fold(placeholder[BigInt](63), {(tuple41: (BigInt, (Coll[BigInt], Boolean))) => tuple41._1 + tuple41._2._1(i39) }) })\n val box40 = OUTPUTS(placeholder[Int](64))\n val coll41 = box40.R5[Coll[Long]].get\n val coll42 = box40.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple43 = coll42(placeholder[Int](65))\n val coll44 = tuple43._1.digest\n val coll45 = box40.R4[Coll[AvlTree]].get\n val box46 = OUTPUTS(placeholder[Int](66))\n val bool47 = tuple43._2 == avlTree34\n val bool48 = coll42.slice(placeholder[Int](67), coll42.size) == coll17.slice(placeholder[Int](68), coll17.size)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](69))._1 == placeholder[Coll[Byte]](70), coll3(placeholder[Int](71))._1 == coll4(placeholder[Int](72)).get.slice(\n placeholder[Int](73), placeholder[Int](74)\n ), allOf(coll7.map({(i49: Int) =>\n val coll51 = coll16(i49)\n if (coll51(placeholder[Int](75)) >= placeholder[Long](76)) {(\n val coll52 = coll36.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll20(i49).toBigInt * bi54 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](77)) { coll35(i49)._1.toBigInt * bi54 / l23.toBigInt * coll24(placeholder[Int](78)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](79)) { coll35(i49)._2.toBigInt * bi54 / l26.toBigInt * coll27(placeholder[Int](80)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll37(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple38 }._2\n })), coll10(placeholder[Int](81)).toBigInt + coll39(placeholder[Int](82)) == coll41(placeholder[Int](83)).toBigInt, avlTree19.remove(\n coll6, getVar[Coll[Byte]](4.toByte).get\n ).get.digest == coll44, avlTree9.update(\n coll5.filter(\n {(tuple49: (Coll[Byte], Coll[Byte])) => byteArrayToLong(tuple49._2.slice(placeholder[Int](84), placeholder[Int](85))) > placeholder[Long](86) }\n ), getVar[Coll[Byte]](6.toByte).get\n ).get.digest == coll45(placeholder[Int](87)).digest, allOf(\n Coll[Boolean](\n blake2b256(box46.propositionBytes) == coll4(placeholder[Int](88)).get.slice(placeholder[Int](89), placeholder[Int](90)), box46.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n box40.value == box2.value, box40.tokens == coll3, coll45(placeholder[Int](91)).digest == coll8(placeholder[Int](92)).digest, bool47, bool48, coll41(\n placeholder[Int](93)\n ) == coll10(placeholder[Int](94)), coll41.slice(placeholder[Int](95), placeholder[Int](96)) == coll10.slice(\n placeholder[Int](97), placeholder[Int](98)\n ), box40.R6[Coll[Coll[Long]]].get == coll21, bool48, bool47, box40.R8[Coll[Long]].get == coll36\n )\n ), (coll5.size >= placeholder[Int](99)) || (\n coll44 == Coll[Byte](\n placeholder[Byte](100), placeholder[Byte](101), placeholder[Byte](102), placeholder[Byte](103), placeholder[Byte](104), placeholder[Byte](\n 105\n ), placeholder[Byte](106), placeholder[Byte](107), placeholder[Byte](108), placeholder[Byte](109), placeholder[Byte](110), placeholder[Byte](\n 111\n ), placeholder[Byte](112), placeholder[Byte](113), placeholder[Byte](114), placeholder[Byte](115), placeholder[Byte](116), placeholder[Byte](\n 117\n ), placeholder[Byte](118), placeholder[Byte](119), placeholder[Byte](120), placeholder[Byte](121), placeholder[Byte](122), placeholder[Byte](\n 123\n ), placeholder[Byte](124), placeholder[Byte](125), placeholder[Byte](126), placeholder[Byte](127), placeholder[Byte](128), placeholder[Byte](\n 129\n ), placeholder[Byte](130), placeholder[Byte](131), placeholder[Byte](132)\n )\n ), coll15.forall({(i49: Int) => coll41.slice(placeholder[Int](133), coll41.size)(i49).toBigInt == coll14(i49).toBigInt - coll39(i49) })\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "10bcaf3cd8906446a14dd467700f1276b4af8b7d771d65924ff99502a4f9b1ba",
"mainChain": true
},
{
"boxId": "34c0134cb9c40d75b8ce1abb0df3cfb5ecf5d6bb7791926e5ca2c66ee8ad3190",
"transactionId": "387bd2db14877e281e08c9ee475fdd0b48b4df56d366d575c486822689e35f24",
"blockId": "ebb325effd7cfb17bbea9ba798a2a17755f1e7499f3f652ee981110987e89fd7",
"value": 150000,
"index": 2,
"globalIndex": 41072599,
"creationHeight": 1295018,
"settlementHeight": 1295020,
"ergoTree": "0008cd023812ba777e72f8e606cda4d4faa2288d439a16cd7c462dc12d3e10a317b019e7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3812ba,bc1fbe,...)))}",
"address": "9ewkq1bvnTdmEc7zwmVBxN8rKri8cYNQbgJtMLUxLsFu5AcDCWE",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 100,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "676dd6b1eaf6cbf48e0c3bec39121ffdddafbb01c5aef49e4fa3799802dd1cd9",
"mainChain": true
},
{
"boxId": "e5c35d46a3448fe506cd352ba1dab965376d857369e1f3b8437ffd22b23e7387",
"transactionId": "387bd2db14877e281e08c9ee475fdd0b48b4df56d366d575c486822689e35f24",
"blockId": "ebb325effd7cfb17bbea9ba798a2a17755f1e7499f3f652ee981110987e89fd7",
"value": 4850000,
"index": 3,
"globalIndex": 41072600,
"creationHeight": 1295018,
"settlementHeight": 1295020,
"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": "5c1cc9382b5984eca7f8a2006841730fd35d656561cda37ea00831ee0cd47bb8",
"mainChain": true
},
{
"boxId": "18ab6634d35992cc431d93e6ca4fe79f3c2b6be6729d738b99a376bb846aa31f",
"transactionId": "387bd2db14877e281e08c9ee475fdd0b48b4df56d366d575c486822689e35f24",
"blockId": "ebb325effd7cfb17bbea9ba798a2a17755f1e7499f3f652ee981110987e89fd7",
"value": 50209000000,
"index": 4,
"globalIndex": 41072601,
"creationHeight": 1295018,
"settlementHeight": 1295020,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(91,-117,93,112,-70,-63,71,-15,-126,-107,12,-61,82,-95,-86,-66,121,-55,-61,-90,101,0,-87,104,76,30,-15,-126,-3,-73,71,63)\n3: false\n4: Coll(0,64,-82,101,12,78,-41,123,-51,32,57,20,-109,-85,-24,76,26,-101,-75,-114,-24,-114,-121,-15,86,112,-56,1,-30,-4,89,-125)\n5: Coll(91,-49,-15,2,37,67,102,120,12,-43,25,18,87,5,10,110,-45,58,-59,-47,46,-17,14,48,65,57,-19,93,-104,31,75,-6)\n6: 0\n7: 0\n8: 0\n9: 1\n10: 0\n11: 0\n12: 0\n13: 0\n14: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n15: Coll(79,-40,-80,-42,-39,-126,66,114,111,87,-77,-33,-90,-122,18,103,-110,-72,-27,5,110,29,81,-74,-23,13,104,-128,-49,45,-51,-59)\n16: 0\n17: 0\n18: Coll(34,94,63,-59,-47,-119,-11,71,-39,-58,38,-66,-67,-58,113,57,-117,108,0,124,120,61,-60,127,-112,63,36,-65,127,52,-124,121)\n19: Coll(-68,74,90,-71,-28,90,-73,75,121,-6,-20,-65,103,73,108,-62,-65,-116,43,14,85,-37,-24,-84,-49,-61,-99,20,-119,17,116,-112)\n20: Coll(118,124,-86,-128,-71,-114,73,106,-40,-87,-10,-119,-60,65,10,-28,83,50,127,15,-107,-23,80,-124,-64,-82,32,99,80,121,59,119)\n21: 0\n22: 1\n23: 9\n24: 2\n25: 1\n26: 2\n27: 1\n28: 33\n29: 0\n30: 0\n31: 3\n32: 1\n33: 9\n34: 0\n35: 0\n36: 1\n37: 1\n38: 9\n39: 1\n40: 1\n41: 1\n42: 33\n43: Coll(-20,-14,-48,75,-82,72,-96,10,-118,110,73,-64,86,114,99,-55,-11,-46,63,38,-56,35,88,-95,118,-85,-47,-16,33,-40,-79,48)\n44: 1\n45: 1\n46: 9\n47: 0\n48: 0\n49: 0\n50: 1\n51: 9\n52: 1\n53: 0\n54: 1\n55: 33\n56: 1\n57: 1\n58: false",
"ergoTreeScript": "{\n val bool1 = INPUTS.exists({(box1: Box) =>\n val coll3 = box1.tokens\n if (coll3.size > placeholder[Int](0)) { coll3(placeholder[Int](1))._1 == placeholder[Coll[Byte]](2) } else { placeholder[Boolean](3) }\n })\n val coll2 = placeholder[Coll[Byte]](4)\n val coll3 = placeholder[Coll[Byte]](5)\n sigmaProp(anyOf(Coll[Boolean](bool1, if (!bool1) {(\n val box4 = OUTPUTS(placeholder[Int](6))\n val coll5 = box4.R5[Coll[Long]].get\n val box6 = INPUTS(placeholder[Int](7))\n val coll7 = SELF.propositionBytes\n val box8 = OUTPUTS.filter({(box8: Box) => box8.propositionBytes == coll7 })(placeholder[Int](8))\n val coll9 = CONTEXT.dataInputs\n val avlTree10 = coll9(placeholder[Int](9)).R4[AvlTree].get\n val coll11 = getVar[Coll[Byte]](0.toByte).get\n val coll12 = INPUTS.filter({(box12: Box) => box12.propositionBytes == coll7 })\n val l13 = coll12.fold(placeholder[Long](10), {(tuple13: (Long, Box)) => tuple13._1 + tuple13._2.value })\n val coll14 = box8.tokens\n val func15 = {(coll15: Coll[Byte]) => coll12.flatMap({(box17: Box) => box17.tokens }).fold(placeholder[Long](11), {(tuple17: (Long, (Coll[Byte], Long))) =>\n val tuple19 = tuple17._2\n tuple17._1 + if (tuple19._1 == coll15) { tuple19._2 } else { placeholder[Long](12) }\n }) }\n val l16 = func15(coll2)\n val coll17 = coll9(placeholder[Int](13)).R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](14), placeholder[Coll[Byte]](15)), getVar[Coll[Byte]](1.toByte).get)\n val bool18 = coll14.filter({(tuple18: (Coll[Byte], Long)) => tuple18._1 != coll2 }).forall({(tuple18: (Coll[Byte], Long)) => tuple18._2 == func15(tuple18._1) })\n val bool19 = coll12.flatMap({(box19: Box) => box19.tokens }).forall({(tuple19: (Coll[Byte], Long)) =>\n val coll21 = tuple19._1\n (coll21 == coll2) || box8.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 })\n })\n if (coll5(placeholder[Int](16)) > box6.R5[Coll[Long]].get(placeholder[Int](17))) {(\n val coll20 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](18), placeholder[Coll[Byte]](19), placeholder[Coll[Byte]](20), coll3), coll11)\n val l21 = byteArrayToLong(coll20(placeholder[Int](21)).get.slice(placeholder[Int](22), placeholder[Int](23))) * coll5(placeholder[Int](24)) + placeholder[Long](25)\n val tuple22 = OUTPUTS.filter({(box22: Box) => blake2b256(box22.propositionBytes) == coll20(placeholder[Int](26)).get.slice(placeholder[Int](27), placeholder[Int](28)) })(placeholder[Int](29)).tokens(placeholder[Int](30))\n allOf(Coll[Boolean](box8.value >= l13 - byteArrayToLong(coll20(placeholder[Int](31)).get.slice(placeholder[Int](32), placeholder[Int](33))), coll14.fold(placeholder[Long](34), {(tuple23: (Long, (Coll[Byte], Long))) =>\n val tuple25 = tuple23._2\n tuple23._1 + if (tuple25._1 == coll2) { tuple25._2 } else { placeholder[Long](35) }\n }) >= l16 - l21 - byteArrayToLong(coll20(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38))), bool18, bool19, tuple22._1 == coll2, tuple22._2 >= l21, blake2b256(INPUTS(placeholder[Int](39)).propositionBytes) == coll17(placeholder[Int](40)).get.slice(placeholder[Int](41), placeholder[Int](42))))\n )} else {(\n val coll20 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](43), coll3), coll11)\n allOf(Coll[Boolean](box8.value >= l13 - byteArrayToLong(coll20(placeholder[Int](44)).get.slice(placeholder[Int](45), placeholder[Int](46))), coll14.fold(placeholder[Long](47), {(tuple21: (Long, (Coll[Byte], Long))) =>\n val tuple23 = tuple21._2\n tuple21._1 + if (tuple23._1 == coll2) { tuple23._2 } else { placeholder[Long](48) }\n }) >= l16 - byteArrayToLong(coll20(placeholder[Int](49)).get.slice(placeholder[Int](50), placeholder[Int](51))), bool18, bool19, blake2b256(INPUTS(placeholder[Int](52)).propositionBytes) == coll17(placeholder[Int](53)).get.slice(placeholder[Int](54), placeholder[Int](55)), box4.tokens(placeholder[Int](56))._2 == box6.tokens(placeholder[Int](57))._2))\n )}\n )} else { placeholder[Boolean](58) })))\n}",
"address": "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",
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{
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"index": 0,
"amount": 1071511583,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
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{
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"index": 1,
"amount": 99948,
"name": "Sigmanaut",
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}
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"spentTransactionId": "51f1091a352adbedd3f54f0a8994bf40de5bca82a7980fcc7f3b28f8634b147f",
"mainChain": true
}
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"size": 18247,
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