Transaction
ID: d3a78b509d...b361
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
14,539.31 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00004 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0005 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
4.93 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
14,539.26 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.047790004 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001249996 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
4.93 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 364,240
Total coins transferred: 14,544.24 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000261 ERG
Raw Transaction Data
{
"id": "d3a78b509d567ada2da31feff30913c613aff3d4fb7835f9bcef19d58681b361",
"blockId": "cbc2e571e3ed5cef7b9705542d56d739ebeb21ac7eecec02b43343c6e936568b",
"inclusionHeight": 1391777,
"timestamp": 1731133316512,
"index": 2,
"globalIndex": 8023431,
"numConfirmations": 364240,
"inputs": [
{
"boxId": "9d33a470175c6472284c334de5237bed131f4306d97ed6ed42488a7874875480",
"value": 14539308964000,
"index": 0,
"spendingProof": null,
"outputBlockId": "a14dfde1caa0e226f57e86e7b19bef50851cb688fc78cd7a1f2d43ec94581d3b",
"outputTransactionId": "7412c127d6e98dbeac371f28393c8b437b78ebe644486bae53cfcdce12fd89ab",
"outputIndex": 0,
"outputGlobalIndex": 43744578,
"outputCreatedAt": 1391768,
"outputSettledAt": 1391770,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 1\n3: 2\n4: 2\n5: 0\n6: 0\n7: CBigInt(1000000000)\n8: CBigInt(1000)\n9: 1000000\n10: CBigInt(66)\n11: CBigInt(100)\n12: 0\n13: CBigInt(4)\n14: CBigInt(0)\n15: CBigInt(5)\n16: Coll(16,37,4,0,4,0,4,2,4,2,4,2,4,0,14,32,-47,-55,-30,6,87,-76,-29,125,-29,-51,39,-102,-103,66,102,-37,52,-79,-114,110,120,99,113,-125,42,-48,20,-3,70,88,49,-104,4,4,4,0,4,0,4,0,4,2,14,32,123,-94,-88,95,-37,48,42,24,21,120,-79,-10,76,-76,-91,51,-40,-101,63,-115,-28,21,-98,-2,-50,117,-38,65,4,21,55,-7,5,0,4,4,5,-56,1,5)\n17: CBigInt(1)\n18: 1\n19: 0\n20: 1\n21: 2\n22: 3\n23: CBigInt(1000000)\n24: true\n25: 3\n26: 4\n27: CBigInt(1000000)\n28: true\n29: true\n30: 1\n31: 0\n32: Coll(17,-102,6,-118,1,25,103,13,-24,-91,-46,70,125,-93,61,-11,114,-112,60,100,-86,-89,-74,-22,76,-106,104,-17,12,-2,3,37)\n33: CBigInt(1000000)\n34: true\n35: true\n36: 0\n37: true\n38: CBigInt(200)\n39: true\n40: 720\n41: 0\n42: 0\n43: 14\n44: CBigInt(200)\n45: CBigInt(2)\n46: true\n47: 14\n48: 0\n49: 0\n50: 0\n51: 14\n52: 0\n53: 1\n54: 14\n55: 1\n56: 14\n57: 1\n58: 0\n59: 14\n60: 0\n61: 0\n62: 0\n63: 14\n64: 0\n65: 1\n66: 14\n67: 1\n68: 14\n69: 1\n70: 0\n71: 720\n72: 720\n73: 720\n74: 14\n75: 14\n76: 0\n77: 0\n78: 14\n79: true\n80: CBigInt(200)\n81: CBigInt(2)\n82: 14\n83: 0\n84: 0\n85: 0\n86: 14\n87: 0\n88: 1\n89: 14\n90: 1\n91: 14\n92: 1\n93: 0\n94: 14\n95: 0\n96: 0\n97: 0\n98: 14\n99: 0\n100: 1\n101: 14\n102: 1\n103: 14\n104: 1\n105: 0\n106: 720\n107: 720\n108: false\n109: 1\n110: false",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val box2 = OUTPUTS(placeholder[Int](0))\n val coll3 = box2.tokens\n val tuple4 = coll1(placeholder[Int](1))\n val tuple5 = coll3(placeholder[Int](2))\n val tuple6 = coll1(placeholder[Int](3))\n val tuple7 = coll3(placeholder[Int](4))\n val tuple8 = SELF.R4[(Long, Long)].get\n val bool9 = tuple8 == box2.R4[(Long, Long)].get\n val prop10 = SELF.R5[SigmaProp].get\n val prop11 = box2.R5[SigmaProp].get\n val tuple12 = SELF.R6[(Long, Long)].get\n val l13 = tuple12._2\n val tuple14 = box2.R6[(Long, Long)].get\n val l15 = tuple14._2\n val bool16 = allOf(\n Coll[Boolean](\n coll1(placeholder[Int](5))._1 == coll3(\n placeholder[Int](6)\n )._1, tuple4._1 == tuple5._1, tuple6._1 == tuple7._1, SELF.propositionBytes == box2.propositionBytes, bool9, prop10 == prop11, l13 == l15\n )\n )\n val l17 = tuple4._2\n val l18 = tuple5._2\n val bool19 = l17 > l18\n val l20 = tuple6._2\n val l21 = tuple7._2\n val bool22 = l20 > l21\n val l23 = SELF.value\n val l24 = box2.value\n val bool25 = allOf(Coll[Boolean](bool16, bool19, bool22, l23 < l24))\n val bool26 = l17 < l18\n val bool27 = l20 < l21\n val bool28 = allOf(Coll[Boolean](bool16, bool26, bool27, l23 > l24))\n val bool29 = l23 == l24\n val bool30 = allOf(Coll[Boolean](bool16, bool19, bool27, bool29))\n val bool31 = allOf(Coll[Boolean](bool16, bool26, bool22, bool29))\n val l32 = tuple12._1\n val coll33 = prop10.propBytes\n val coll34 = SELF.R7[Coll[Long]].get\n val coll35 = box2.R7[Coll[Long]].get\n val coll36 = SELF.R8[Coll[Long]].get\n val coll37 = box2.R8[Coll[Long]].get\n val l38 = SELF.R9[Long].get\n val l39 = box2.R9[Long].get\n if (anyOf(Coll[Boolean](bool25, bool28, bool30, bool31))) {(\n val bi40 = tuple8._1 - l17.toBigInt\n val bi41 = placeholder[BigInt](7)\n val bi42 = placeholder[BigInt](8)\n val bi43 = l23 - placeholder[Long](9).toBigInt\n val bi44 = tuple8._2 - l20.toBigInt\n val opt45 = getVar[SigmaProp](0.toByte)\n val bi46 = min(\n placeholder[BigInt](10) * bi41 / placeholder[BigInt](11), bi40 * CONTEXT.dataInputs(placeholder[Int](12)).R4[Long].get.toBigInt / bi42 / bi43\n )\n val bi47 = bi41 - bi46\n val func48 = {(l48: Long) => l48.toBigInt * bi47 * bi43 / bi44 / bi41 }\n val func49 = {(l49: Long) => l49.toBigInt * bi46 * bi43 / bi40 / bi41 }\n val bi50 = if (bool25) { l24 - l23.toBigInt } else {\n if (bool28) { l23 - l24.toBigInt } else { if (bool30) { func48(l21 - l20) } else { func49(l18 - l17) } }\n }\n val bi51 = placeholder[BigInt](13) * bi50 / bi42\n val bi52 = placeholder[BigInt](14)\n val tuple53 = (coll33, if (l32 < l13) { placeholder[BigInt](15) * bi50 / bi42 * l13 - l32.toBigInt / l13.toBigInt } else { bi52 })\n val tuple54 = (placeholder[Coll[Byte]](16), placeholder[BigInt](17) * bi50 / bi42)\n val tuple55 = (Coll[Byte](placeholder[Byte](18)), bi52)\n val coll56 = if (bool31 || bool30) {\n if (opt45.isDefined) { Coll[(Coll[Byte], BigInt)](tuple53, tuple54, (opt45.get.propBytes, bi51)) } else {\n Coll[(Coll[Byte], BigInt)](tuple53, tuple54, tuple55)\n }\n } else {\n if (opt45.isDefined) { Coll[(Coll[Byte], BigInt)](tuple53, (opt45.get.propBytes, bi51), tuple55) } else {\n Coll[(Coll[Byte], BigInt)](tuple53, tuple55, tuple55)\n }\n }\n val tuple57 = coll56(placeholder[Int](19))\n val bi58 = tuple57._2\n val tuple59 = coll56(placeholder[Int](20))\n val bi60 = tuple59._2\n val box61 = OUTPUTS(placeholder[Int](21))\n val coll62 = tuple59._1\n val bool63 = bi60 > bi52\n val bool64 = allOf(Coll[Boolean]((if (bi58 > bi52) {(\n val box64 = if (bi60 <= bi52) { box61 } else { OUTPUTS(placeholder[Int](22)) }\n allOf(Coll[Boolean](box64.propositionBytes == tuple57._1, box64.value.toBigInt == bi58 + placeholder[BigInt](23)))\n )} else { placeholder[Boolean](24) } && if (opt45.isDefined) { if (bool63) {(\n val box64 = if (bi60 <= bi52) { OUTPUTS(placeholder[Int](25)) } else { OUTPUTS(placeholder[Int](26)) }\n allOf(Coll[Boolean](box64.propositionBytes == coll62, box64.value.toBigInt == bi60 + placeholder[BigInt](27)))\n )} else { placeholder[Boolean](28) } } else { placeholder[Boolean](29) }) && if (bool30 || bool31) { if (bool63) {(\n val coll64 = box61.propositionBytes\n val box65 = INPUTS(INPUTS.size - placeholder[Int](30))\n allOf(Coll[Boolean](coll64 == coll62, coll64 == box65.propositionBytes, box61.tokens(placeholder[Int](31))._1 == placeholder[Coll[Byte]](32), box61.value.toBigInt == box65.value.toBigInt + bi60 + placeholder[BigInt](33)))\n )} else { placeholder[Boolean](34) } } else { placeholder[Boolean](35) }, tuple14._1 - l32.toBigInt == bi58, l15 == l13))\n val bool65 = allOf(Coll[Boolean](coll34 == coll35, coll36 == coll37, l38 == l39))\n val func66 = {(coll66: Coll[Long]) => coll66.fold(placeholder[Long](36), {(tuple68: (Long, Long)) => tuple68._1 + tuple68._2 }).toBigInt }\n if (bool25) {(\n val bi67 = l24 - l23.toBigInt\n val bi68 = bi41 - bi41 / bi42\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool16, l17 - l18.toBigInt == bi67 * bi40 * bi68 / bi43 / bi41, l20 - l21.toBigInt == bi67 * bi44 * bi68 / bi43 / bi41, placeholder[Boolean](\n 37\n ), bool64, bool65\n )\n )\n )\n )} else { if (bool28) {(\n val bi67 = l23 - l24.toBigInt\n val bi68 = bi43 * bi41 - bi41 / placeholder[BigInt](38)\n sigmaProp(allOf(Coll[Boolean](bool16, l18 - l17.toBigInt == bi67 * bi40 * bi41 / bi68, l21 - l20.toBigInt == bi67 * bi44 * bi41 / bi68, placeholder[Boolean](39), bool64, bool65)))\n )} else { if (bool30) {(\n val l67 = l21 - l20\n val bi68 = func66(coll37)\n val bi69 = func66(coll35)\n val i70 = HEIGHT.toLong - l38 / placeholder[Int](40).toLong.toInt\n val bool71 = i70 == placeholder[Int](41)\n val bool72 = i70 > placeholder[Int](42)\n val i73 = placeholder[Int](43) - i70\n sigmaProp(allOf(Coll[Boolean](bool16, l17 - l18.toBigInt == l67.toBigInt * bi41 - bi41 / placeholder[BigInt](44) + bi41 / placeholder[BigInt](45) * if (bi68 > bi69) { bi52 } else { bi69 - bi68 } / bi43 / bi44 * bi47 * bi40 / bi41 / bi46, placeholder[Boolean](46), l24.toBigInt == l23.toBigInt, bool64, allOf(Coll[Boolean](coll37.size == placeholder[Int](47), if (bool71) { coll36(placeholder[Int](48)) } else { placeholder[Long](49) } == coll37(placeholder[Int](50)), if (bool72) { coll37.slice(i70, placeholder[Int](51)) == coll36.slice(placeholder[Int](52), i73) } else { coll37.slice(placeholder[Int](53), placeholder[Int](54)) == coll36.slice(placeholder[Int](55), placeholder[Int](56)) }, coll37.slice(placeholder[Int](57), i70).forall({(l74: Long) => l74 == placeholder[Long](58) }))), allOf(Coll[Boolean](coll35.size == placeholder[Int](59), coll35(placeholder[Int](60)).toBigInt == if (bool71) { coll34(placeholder[Int](61)) } else { placeholder[Long](62) }.toBigInt + func48(l67), if (bool72) { coll35.slice(i70, placeholder[Int](63)) == coll34.slice(placeholder[Int](64), i73) } else { coll35.slice(placeholder[Int](65), placeholder[Int](66)) == coll34.slice(placeholder[Int](67), placeholder[Int](68)) }, coll35.slice(placeholder[Int](69), i70).forall({(l74: Long) => l74 == placeholder[Long](70) }))), l39 == HEIGHT / placeholder[Int](71) * placeholder[Int](72).toLong)))\n )} else { if (bool31) {(\n val l67 = l18 - l17\n val bi68 = func66(coll35)\n val bi69 = func66(coll37)\n val i70 = HEIGHT.toLong - l38 / placeholder[Int](73).toLong.toInt\n val i71 = if (i70 >= placeholder[Int](74)) { placeholder[Int](75) } else { i70 }\n val bool72 = i71 == placeholder[Int](76)\n val bool73 = i71 > placeholder[Int](77)\n val i74 = placeholder[Int](78) - i71\n sigmaProp(allOf(Coll[Boolean](bool16, placeholder[Boolean](79), l20 - l21.toBigInt == l67.toBigInt * bi41 - bi41 / placeholder[BigInt](80) + bi41 / placeholder[BigInt](81) * if (bi68 > bi69) { bi52 } else { bi69 - bi68 } / bi43 / bi40 * bi46 * bi44 / bi41 / bi47, l24.toBigInt == l23.toBigInt, bool64, allOf(Coll[Boolean](coll35.size == placeholder[Int](82), if (bool72) { coll34(placeholder[Int](83)) } else { placeholder[Long](84) } == coll35(placeholder[Int](85)), if (bool73) { coll35.slice(i71, placeholder[Int](86)) == coll34.slice(placeholder[Int](87), i74) } else { coll35.slice(placeholder[Int](88), placeholder[Int](89)) == coll34.slice(placeholder[Int](90), placeholder[Int](91)) }, coll35.slice(placeholder[Int](92), i71).forall({(l75: Long) => l75 == placeholder[Long](93) }))), allOf(Coll[Boolean](coll37.size == placeholder[Int](94), coll37(placeholder[Int](95)).toBigInt == if (bool72) { coll36(placeholder[Int](96)) } else { placeholder[Long](97) }.toBigInt + func49(l67), if (bool73) { coll37.slice(i71, placeholder[Int](98)) == coll36.slice(placeholder[Int](99), i74) } else { coll37.slice(placeholder[Int](100), placeholder[Int](101)) == coll36.slice(placeholder[Int](102), placeholder[Int](103)) }, coll37.slice(placeholder[Int](104), i71).forall({(l75: Long) => l75 == placeholder[Long](105) }))), l39 == HEIGHT / placeholder[Int](106) * placeholder[Int](107).toLong)))\n )} else { sigmaProp(placeholder[Boolean](108)) } } } }\n )} else {\n if (INPUTS(placeholder[Int](109)).propositionBytes == coll33) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(Coll[Boolean](bool29, coll1 == coll3, bool9, tuple12 == tuple14, coll34 == coll35, coll36 == coll37, l38 == l39)), prop11 != prop10\n )\n )\n ) && prop10\n } else { sigmaProp(placeholder[Boolean](110)) }\n }\n}",
"address": "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",
"assets": [
{
"tokenId": "797e331df22c5cfd0aae654703ebc12dcbcba99b80d32e2b7e151eac2d27b6fa",
"index": 0,
"amount": 1,
"name": "GluonW NFT",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "886b7721bef42f60c6317d37d8752da8aca01898cae7dae61808c4a14225edc8",
"index": 1,
"amount": 99999924705158130,
"name": "GluonW GAU",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "9944ff273ff169f32b851b96bbecdbb67f223101c15ae143de82b3e7f75b19d2",
"index": 2,
"amount": 99999985622167870,
"name": "GluonW GAUC",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "08cd026e755ff74926eab1986ad39bce2bdb9264d6c0a62835e991459840e22e57191f",
"sigmaType": "SSigmaProp",
"renderedValue": "026e755ff74926eab1986ad39bce2bdb9264d6c0a62835e991459840e22e57191f"
},
"R6": {
"serializedValue": "599680d8918d07808088fccdbcc323",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[122022461451,10000000000000000]"
},
"R8": {
"serializedValue": "110eec83c7bbd40500009c99c79d35000000000000beb3b19cb201000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[97236082934,0,0,7144531534,0,0,0,0,0,0,23920520415,0,0,0]"
},
"R7": {
"serializedValue": "110ececda8fd8307e6cdea80a50186c9cbcfb00200b2dbd1909d040000000000feeec2a5b501000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[120793142119,22146798451,40885645891,0,72629237465,0,0,0,0,0,24332753855,0,0,0]"
},
"R9": {
"serializedValue": "0580e7a901",
"sigmaType": "SLong",
"renderedValue": "1391040"
},
"R4": {
"serializedValue": "598080d0d88bdea2e3028080d0d88bdea2e302",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[100000000000000000,100000000000000000]"
}
}
},
{
"boxId": "a07e0137ce6814c89040cdf9c8b0ae0028ad18a56d62250caed77f9495bfe881",
"value": 40000,
"index": 1,
"spendingProof": "8fe543f987717e4a85fecc7e8e633ca93141b54db4558c5bf4b0f7c271ab61b7815f93f4410f904cbc4a19109f2efa4c103845c2fc866c21",
"outputBlockId": "f03c1ad8f73189e6b50cac79797e533b8864158ebf86b780dfc39adead1f5a36",
"outputTransactionId": "e206b94e4c037deed414791e8ab891268cf7e83d1fd9b34a86ab8d24989036d0",
"outputIndex": 1771,
"outputGlobalIndex": 32800592,
"outputCreatedAt": 1094094,
"outputSettledAt": 1094235,
"ergoTree": "0008cd037c84abab2871332cb64b0646addf107a8d25a823f69c64b993ef6943367ac717",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(7c84ab,a45399,...)))}",
"address": "9hQeLqfkbNESaU1QfuaDENAL8Cdv6k9BgYA9MZwa2Nqhz4zxnhp",
"assets": [
{
"tokenId": "0fdb7ff8b37479b6eb7aab38d45af2cfeefabbefdc7eebc0348d25dd65bc2c91",
"index": 0,
"amount": 69,
"name": "$Lambo",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "a19bfbd1fec65eb8c7ece9a2f7fbbdd4a83a3c6914e3151fa33bd197d4e5e77f",
"value": 500000,
"index": 2,
"spendingProof": "1387be04a587c82d9a8f5a633bc8f53e6bf19869f8640ba2b4f504ea1f73ed433e1a918eed6f32eec88ab8b36f77b9055aa529fd0a8075ac",
"outputBlockId": "d679853a1d3c552ed77cbd731f297916256a6ac5ef498557916326416a366c4a",
"outputTransactionId": "313adaddea063e4b90ab6a9579ba5dab954516b10fdb35efcfe04d1550e2d4be",
"outputIndex": 251,
"outputGlobalIndex": 38810064,
"outputCreatedAt": 1237252,
"outputSettledAt": 1237261,
"ergoTree": "0008cd037c84abab2871332cb64b0646addf107a8d25a823f69c64b993ef6943367ac717",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(7c84ab,a45399,...)))}",
"address": "9hQeLqfkbNESaU1QfuaDENAL8Cdv6k9BgYA9MZwa2Nqhz4zxnhp",
"assets": [
{
"tokenId": "af1a2e8005f6ffc9e291e121d1fb08795c5a079409b8ca56e20eb2f4f6f8553b",
"index": 0,
"amount": 4200000000,
"name": "🐶",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "baf1684564bc3e6adc7faeccf134d3f2d755af466df990494f045d2595694fec",
"value": 4926399636,
"index": 3,
"spendingProof": "a047ebf0ca9c4420f2b3df3a37e5770800b56e01bad76fbeeb2624c4c8acae7059937f323437e1bee88568b3174de0f390e8eb2f042d326d",
"outputBlockId": "a14dfde1caa0e226f57e86e7b19bef50851cb688fc78cd7a1f2d43ec94581d3b",
"outputTransactionId": "7412c127d6e98dbeac371f28393c8b437b78ebe644486bae53cfcdce12fd89ab",
"outputIndex": 1,
"outputGlobalIndex": 43744579,
"outputCreatedAt": 1391768,
"outputSettledAt": 1391770,
"ergoTree": "0008cd037c84abab2871332cb64b0646addf107a8d25a823f69c64b993ef6943367ac717",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(7c84ab,a45399,...)))}",
"address": "9hQeLqfkbNESaU1QfuaDENAL8Cdv6k9BgYA9MZwa2Nqhz4zxnhp",
"assets": [
{
"tokenId": "abaf9df62c6810b0198333b122d130c29d76d64c6d7f4d57108afc5aaa95efb5",
"index": 0,
"amount": 1487293614,
"name": "AirdropTest",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 1,
"amount": 424150,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "22342ca384aa15022c311d0f46835c6df1d6df2f2e68a03f0e1e5952a4447939",
"index": 2,
"amount": 1,
"name": "The Djed Stablecoin Protocol Explained in a Single Image ",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "886b7721bef42f60c6317d37d8752da8aca01898cae7dae61808c4a14225edc8",
"index": 3,
"amount": 569088,
"name": "GluonW GAU",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "9944ff273ff169f32b851b96bbecdbb67f223101c15ae143de82b3e7f75b19d2",
"index": 4,
"amount": 108669,
"name": "GluonW GAUC",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "4642959870029e83cc9a558b85af5ad7c84880ecbc313a6aa82a3cc177180fec",
"value": 10000000,
"index": 0,
"outputBlockId": "7fc47d2544e488e32c4645dc82f2409ddef12daa067e858d5dd2d2a6a34ec63e",
"outputTransactionId": "ae99f383600206f9146742a5ecee6b1657456d18e9a9923ac6b939a21b0ab432",
"outputIndex": 0,
"ergoTree": "1004040204000e2097ad159235d25d05d7efc5863b5d360f89d7d668409502058be3e7aac177b9cb0e20a40bedb08a32c0258405f950af5a133c397630f89f7d31fb00b3ab9811d29e6ad801d6018cb2db6308b2a473000073010001d1ec93720173029372017303",
"address": "PViBL5acX6PqzhnRzKkXN48Rr2SNWspChGAVUHFtGjhNK7dzGm3VeJdkgvzySx5uSWsyekihaxdVpuvhz4MqNZjU8FkwYZUzUC8AL3pFNifisCSrLywNWehhxGz8EJpyuCdtofhUFVw6qNEsvCP2",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "05f4d7bdb6e6f126",
"sigmaType": "SLong",
"renderedValue": "85517956265466"
},
"R5": {
"serializedValue": "04a09201",
"sigmaType": "SInt",
"renderedValue": "9360"
}
}
}
],
"outputs": [
{
"boxId": "73dcfb02f239eaf5781234fbe63665c62ab1376bcaa3d59391e3038f4a3a7ddd",
"transactionId": "d3a78b509d567ada2da31feff30913c613aff3d4fb7835f9bcef19d58681b361",
"blockId": "cbc2e571e3ed5cef7b9705542d56d739ebeb21ac7eecec02b43343c6e936568b",
"value": 14539258964000,
"index": 0,
"globalIndex": 43744865,
"creationHeight": 1391774,
"settlementHeight": 1391777,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 1\n3: 2\n4: 2\n5: 0\n6: 0\n7: CBigInt(1000000000)\n8: CBigInt(1000)\n9: 1000000\n10: CBigInt(66)\n11: CBigInt(100)\n12: 0\n13: CBigInt(4)\n14: CBigInt(0)\n15: CBigInt(5)\n16: Coll(16,37,4,0,4,0,4,2,4,2,4,2,4,0,14,32,-47,-55,-30,6,87,-76,-29,125,-29,-51,39,-102,-103,66,102,-37,52,-79,-114,110,120,99,113,-125,42,-48,20,-3,70,88,49,-104,4,4,4,0,4,0,4,0,4,2,14,32,123,-94,-88,95,-37,48,42,24,21,120,-79,-10,76,-76,-91,51,-40,-101,63,-115,-28,21,-98,-2,-50,117,-38,65,4,21,55,-7,5,0,4,4,5,-56,1,5)\n17: CBigInt(1)\n18: 1\n19: 0\n20: 1\n21: 2\n22: 3\n23: CBigInt(1000000)\n24: true\n25: 3\n26: 4\n27: CBigInt(1000000)\n28: true\n29: true\n30: 1\n31: 0\n32: Coll(17,-102,6,-118,1,25,103,13,-24,-91,-46,70,125,-93,61,-11,114,-112,60,100,-86,-89,-74,-22,76,-106,104,-17,12,-2,3,37)\n33: CBigInt(1000000)\n34: true\n35: true\n36: 0\n37: true\n38: CBigInt(200)\n39: true\n40: 720\n41: 0\n42: 0\n43: 14\n44: CBigInt(200)\n45: CBigInt(2)\n46: true\n47: 14\n48: 0\n49: 0\n50: 0\n51: 14\n52: 0\n53: 1\n54: 14\n55: 1\n56: 14\n57: 1\n58: 0\n59: 14\n60: 0\n61: 0\n62: 0\n63: 14\n64: 0\n65: 1\n66: 14\n67: 1\n68: 14\n69: 1\n70: 0\n71: 720\n72: 720\n73: 720\n74: 14\n75: 14\n76: 0\n77: 0\n78: 14\n79: true\n80: CBigInt(200)\n81: CBigInt(2)\n82: 14\n83: 0\n84: 0\n85: 0\n86: 14\n87: 0\n88: 1\n89: 14\n90: 1\n91: 14\n92: 1\n93: 0\n94: 14\n95: 0\n96: 0\n97: 0\n98: 14\n99: 0\n100: 1\n101: 14\n102: 1\n103: 14\n104: 1\n105: 0\n106: 720\n107: 720\n108: false\n109: 1\n110: false",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val box2 = OUTPUTS(placeholder[Int](0))\n val coll3 = box2.tokens\n val tuple4 = coll1(placeholder[Int](1))\n val tuple5 = coll3(placeholder[Int](2))\n val tuple6 = coll1(placeholder[Int](3))\n val tuple7 = coll3(placeholder[Int](4))\n val tuple8 = SELF.R4[(Long, Long)].get\n val bool9 = tuple8 == box2.R4[(Long, Long)].get\n val prop10 = SELF.R5[SigmaProp].get\n val prop11 = box2.R5[SigmaProp].get\n val tuple12 = SELF.R6[(Long, Long)].get\n val l13 = tuple12._2\n val tuple14 = box2.R6[(Long, Long)].get\n val l15 = tuple14._2\n val bool16 = allOf(\n Coll[Boolean](\n coll1(placeholder[Int](5))._1 == coll3(\n placeholder[Int](6)\n )._1, tuple4._1 == tuple5._1, tuple6._1 == tuple7._1, SELF.propositionBytes == box2.propositionBytes, bool9, prop10 == prop11, l13 == l15\n )\n )\n val l17 = tuple4._2\n val l18 = tuple5._2\n val bool19 = l17 > l18\n val l20 = tuple6._2\n val l21 = tuple7._2\n val bool22 = l20 > l21\n val l23 = SELF.value\n val l24 = box2.value\n val bool25 = allOf(Coll[Boolean](bool16, bool19, bool22, l23 < l24))\n val bool26 = l17 < l18\n val bool27 = l20 < l21\n val bool28 = allOf(Coll[Boolean](bool16, bool26, bool27, l23 > l24))\n val bool29 = l23 == l24\n val bool30 = allOf(Coll[Boolean](bool16, bool19, bool27, bool29))\n val bool31 = allOf(Coll[Boolean](bool16, bool26, bool22, bool29))\n val l32 = tuple12._1\n val coll33 = prop10.propBytes\n val coll34 = SELF.R7[Coll[Long]].get\n val coll35 = box2.R7[Coll[Long]].get\n val coll36 = SELF.R8[Coll[Long]].get\n val coll37 = box2.R8[Coll[Long]].get\n val l38 = SELF.R9[Long].get\n val l39 = box2.R9[Long].get\n if (anyOf(Coll[Boolean](bool25, bool28, bool30, bool31))) {(\n val bi40 = tuple8._1 - l17.toBigInt\n val bi41 = placeholder[BigInt](7)\n val bi42 = placeholder[BigInt](8)\n val bi43 = l23 - placeholder[Long](9).toBigInt\n val bi44 = tuple8._2 - l20.toBigInt\n val opt45 = getVar[SigmaProp](0.toByte)\n val bi46 = min(\n placeholder[BigInt](10) * bi41 / placeholder[BigInt](11), bi40 * CONTEXT.dataInputs(placeholder[Int](12)).R4[Long].get.toBigInt / bi42 / bi43\n )\n val bi47 = bi41 - bi46\n val func48 = {(l48: Long) => l48.toBigInt * bi47 * bi43 / bi44 / bi41 }\n val func49 = {(l49: Long) => l49.toBigInt * bi46 * bi43 / bi40 / bi41 }\n val bi50 = if (bool25) { l24 - l23.toBigInt } else {\n if (bool28) { l23 - l24.toBigInt } else { if (bool30) { func48(l21 - l20) } else { func49(l18 - l17) } }\n }\n val bi51 = placeholder[BigInt](13) * bi50 / bi42\n val bi52 = placeholder[BigInt](14)\n val tuple53 = (coll33, if (l32 < l13) { placeholder[BigInt](15) * bi50 / bi42 * l13 - l32.toBigInt / l13.toBigInt } else { bi52 })\n val tuple54 = (placeholder[Coll[Byte]](16), placeholder[BigInt](17) * bi50 / bi42)\n val tuple55 = (Coll[Byte](placeholder[Byte](18)), bi52)\n val coll56 = if (bool31 || bool30) {\n if (opt45.isDefined) { Coll[(Coll[Byte], BigInt)](tuple53, tuple54, (opt45.get.propBytes, bi51)) } else {\n Coll[(Coll[Byte], BigInt)](tuple53, tuple54, tuple55)\n }\n } else {\n if (opt45.isDefined) { Coll[(Coll[Byte], BigInt)](tuple53, (opt45.get.propBytes, bi51), tuple55) } else {\n Coll[(Coll[Byte], BigInt)](tuple53, tuple55, tuple55)\n }\n }\n val tuple57 = coll56(placeholder[Int](19))\n val bi58 = tuple57._2\n val tuple59 = coll56(placeholder[Int](20))\n val bi60 = tuple59._2\n val box61 = OUTPUTS(placeholder[Int](21))\n val coll62 = tuple59._1\n val bool63 = bi60 > bi52\n val bool64 = allOf(Coll[Boolean]((if (bi58 > bi52) {(\n val box64 = if (bi60 <= bi52) { box61 } else { OUTPUTS(placeholder[Int](22)) }\n allOf(Coll[Boolean](box64.propositionBytes == tuple57._1, box64.value.toBigInt == bi58 + placeholder[BigInt](23)))\n )} else { placeholder[Boolean](24) } && if (opt45.isDefined) { if (bool63) {(\n val box64 = if (bi60 <= bi52) { OUTPUTS(placeholder[Int](25)) } else { OUTPUTS(placeholder[Int](26)) }\n allOf(Coll[Boolean](box64.propositionBytes == coll62, box64.value.toBigInt == bi60 + placeholder[BigInt](27)))\n )} else { placeholder[Boolean](28) } } else { placeholder[Boolean](29) }) && if (bool30 || bool31) { if (bool63) {(\n val coll64 = box61.propositionBytes\n val box65 = INPUTS(INPUTS.size - placeholder[Int](30))\n allOf(Coll[Boolean](coll64 == coll62, coll64 == box65.propositionBytes, box61.tokens(placeholder[Int](31))._1 == placeholder[Coll[Byte]](32), box61.value.toBigInt == box65.value.toBigInt + bi60 + placeholder[BigInt](33)))\n )} else { placeholder[Boolean](34) } } else { placeholder[Boolean](35) }, tuple14._1 - l32.toBigInt == bi58, l15 == l13))\n val bool65 = allOf(Coll[Boolean](coll34 == coll35, coll36 == coll37, l38 == l39))\n val func66 = {(coll66: Coll[Long]) => coll66.fold(placeholder[Long](36), {(tuple68: (Long, Long)) => tuple68._1 + tuple68._2 }).toBigInt }\n if (bool25) {(\n val bi67 = l24 - l23.toBigInt\n val bi68 = bi41 - bi41 / bi42\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool16, l17 - l18.toBigInt == bi67 * bi40 * bi68 / bi43 / bi41, l20 - l21.toBigInt == bi67 * bi44 * bi68 / bi43 / bi41, placeholder[Boolean](\n 37\n ), bool64, bool65\n )\n )\n )\n )} else { if (bool28) {(\n val bi67 = l23 - l24.toBigInt\n val bi68 = bi43 * bi41 - bi41 / placeholder[BigInt](38)\n sigmaProp(allOf(Coll[Boolean](bool16, l18 - l17.toBigInt == bi67 * bi40 * bi41 / bi68, l21 - l20.toBigInt == bi67 * bi44 * bi41 / bi68, placeholder[Boolean](39), bool64, bool65)))\n )} else { if (bool30) {(\n val l67 = l21 - l20\n val bi68 = func66(coll37)\n val bi69 = func66(coll35)\n val i70 = HEIGHT.toLong - l38 / placeholder[Int](40).toLong.toInt\n val bool71 = i70 == placeholder[Int](41)\n val bool72 = i70 > placeholder[Int](42)\n val i73 = placeholder[Int](43) - i70\n sigmaProp(allOf(Coll[Boolean](bool16, l17 - l18.toBigInt == l67.toBigInt * bi41 - bi41 / placeholder[BigInt](44) + bi41 / placeholder[BigInt](45) * if (bi68 > bi69) { bi52 } else { bi69 - bi68 } / bi43 / bi44 * bi47 * bi40 / bi41 / bi46, placeholder[Boolean](46), l24.toBigInt == l23.toBigInt, bool64, allOf(Coll[Boolean](coll37.size == placeholder[Int](47), if (bool71) { coll36(placeholder[Int](48)) } else { placeholder[Long](49) } == coll37(placeholder[Int](50)), if (bool72) { coll37.slice(i70, placeholder[Int](51)) == coll36.slice(placeholder[Int](52), i73) } else { coll37.slice(placeholder[Int](53), placeholder[Int](54)) == coll36.slice(placeholder[Int](55), placeholder[Int](56)) }, coll37.slice(placeholder[Int](57), i70).forall({(l74: Long) => l74 == placeholder[Long](58) }))), allOf(Coll[Boolean](coll35.size == placeholder[Int](59), coll35(placeholder[Int](60)).toBigInt == if (bool71) { coll34(placeholder[Int](61)) } else { placeholder[Long](62) }.toBigInt + func48(l67), if (bool72) { coll35.slice(i70, placeholder[Int](63)) == coll34.slice(placeholder[Int](64), i73) } else { coll35.slice(placeholder[Int](65), placeholder[Int](66)) == coll34.slice(placeholder[Int](67), placeholder[Int](68)) }, coll35.slice(placeholder[Int](69), i70).forall({(l74: Long) => l74 == placeholder[Long](70) }))), l39 == HEIGHT / placeholder[Int](71) * placeholder[Int](72).toLong)))\n )} else { if (bool31) {(\n val l67 = l18 - l17\n val bi68 = func66(coll35)\n val bi69 = func66(coll37)\n val i70 = HEIGHT.toLong - l38 / placeholder[Int](73).toLong.toInt\n val i71 = if (i70 >= placeholder[Int](74)) { placeholder[Int](75) } else { i70 }\n val bool72 = i71 == placeholder[Int](76)\n val bool73 = i71 > placeholder[Int](77)\n val i74 = placeholder[Int](78) - i71\n sigmaProp(allOf(Coll[Boolean](bool16, placeholder[Boolean](79), l20 - l21.toBigInt == l67.toBigInt * bi41 - bi41 / placeholder[BigInt](80) + bi41 / placeholder[BigInt](81) * if (bi68 > bi69) { bi52 } else { bi69 - bi68 } / bi43 / bi40 * bi46 * bi44 / bi41 / bi47, l24.toBigInt == l23.toBigInt, bool64, allOf(Coll[Boolean](coll35.size == placeholder[Int](82), if (bool72) { coll34(placeholder[Int](83)) } else { placeholder[Long](84) } == coll35(placeholder[Int](85)), if (bool73) { coll35.slice(i71, placeholder[Int](86)) == coll34.slice(placeholder[Int](87), i74) } else { coll35.slice(placeholder[Int](88), placeholder[Int](89)) == coll34.slice(placeholder[Int](90), placeholder[Int](91)) }, coll35.slice(placeholder[Int](92), i71).forall({(l75: Long) => l75 == placeholder[Long](93) }))), allOf(Coll[Boolean](coll37.size == placeholder[Int](94), coll37(placeholder[Int](95)).toBigInt == if (bool72) { coll36(placeholder[Int](96)) } else { placeholder[Long](97) }.toBigInt + func49(l67), if (bool73) { coll37.slice(i71, placeholder[Int](98)) == coll36.slice(placeholder[Int](99), i74) } else { coll37.slice(placeholder[Int](100), placeholder[Int](101)) == coll36.slice(placeholder[Int](102), placeholder[Int](103)) }, coll37.slice(placeholder[Int](104), i71).forall({(l75: Long) => l75 == placeholder[Long](105) }))), l39 == HEIGHT / placeholder[Int](106) * placeholder[Int](107).toLong)))\n )} else { sigmaProp(placeholder[Boolean](108)) } } } }\n )} else {\n if (INPUTS(placeholder[Int](109)).propositionBytes == coll33) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(Coll[Boolean](bool29, coll1 == coll3, bool9, tuple12 == tuple14, coll34 == coll35, coll36 == coll37, l38 == l39)), prop11 != prop10\n )\n )\n ) && prop10\n } else { sigmaProp(placeholder[Boolean](110)) }\n }\n}",
"address": "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",
"assets": [
{
"tokenId": "797e331df22c5cfd0aae654703ebc12dcbcba99b80d32e2b7e151eac2d27b6fa",
"index": 0,
"amount": 1,
"name": "GluonW NFT",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "886b7721bef42f60c6317d37d8752da8aca01898cae7dae61808c4a14225edc8",
"index": 1,
"amount": 99999924705418370,
"name": "GluonW GAU",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "9944ff273ff169f32b851b96bbecdbb67f223101c15ae143de82b3e7f75b19d2",
"index": 2,
"amount": 99999985622217570,
"name": "GluonW GAUC",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "08cd026e755ff74926eab1986ad39bce2bdb9264d6c0a62835e991459840e22e57191f",
"sigmaType": "SSigmaProp",
"renderedValue": "026e755ff74926eab1986ad39bce2bdb9264d6c0a62835e991459840e22e57191f"
},
"R6": {
"serializedValue": "59aec2f6918d07808088fccdbcc323",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[122022711447,10000000000000000]"
},
"R8": {
"serializedValue": "110eec83c7bbd40500009c99c79d35000000000000beb3b19cb201000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[97236082934,0,0,7144531534,0,0,0,0,0,0,23920520415,0,0,0]"
},
"R7": {
"serializedValue": "110ececda8fd8307e6cdea80a50186c9cbcfb00200b2dbd1909d040000000000feeec2a5b501000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[120793142119,22146798451,40885645891,0,72629237465,0,0,0,0,0,24332753855,0,0,0]"
},
"R9": {
"serializedValue": "0580e7a901",
"sigmaType": "SLong",
"renderedValue": "1391040"
},
"R4": {
"serializedValue": "598080d0d88bdea2e3028080d0d88bdea2e302",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[100000000000000000,100000000000000000]"
}
},
"spentTransactionId": "9858b6e8fc39096f498374859d9ca362863ce2626f9421f4cd97b0f785a80339",
"mainChain": true
},
{
"boxId": "770d40ae1556439d8a573176a19aebe35c522efc57d99fffd574193ca66e0fc5",
"transactionId": "d3a78b509d567ada2da31feff30913c613aff3d4fb7835f9bcef19d58681b361",
"blockId": "cbc2e571e3ed5cef7b9705542d56d739ebeb21ac7eecec02b43343c6e936568b",
"value": 47790004,
"index": 1,
"globalIndex": 43744866,
"creationHeight": 1391774,
"settlementHeight": 1391777,
"ergoTree": "0008cd037c84abab2871332cb64b0646addf107a8d25a823f69c64b993ef6943367ac717",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(7c84ab,a45399,...)))}",
"address": "9hQeLqfkbNESaU1QfuaDENAL8Cdv6k9BgYA9MZwa2Nqhz4zxnhp",
"assets": [
{
"tokenId": "0fdb7ff8b37479b6eb7aab38d45af2cfeefabbefdc7eebc0348d25dd65bc2c91",
"index": 0,
"amount": 69,
"name": "$Lambo",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "aa900ea0696f5c3899e8643b2c81f254e55974f4f9c1c7730237d752346e91ab",
"mainChain": true
},
{
"boxId": "e18279642e51ef1f96c03ec5d82e81b3b04f9ef74986020a379b3c15eb9c499a",
"transactionId": "d3a78b509d567ada2da31feff30913c613aff3d4fb7835f9bcef19d58681b361",
"blockId": "cbc2e571e3ed5cef7b9705542d56d739ebeb21ac7eecec02b43343c6e936568b",
"value": 1249996,
"index": 2,
"globalIndex": 43744867,
"creationHeight": 1391774,
"settlementHeight": 1391777,
"ergoTree": "0008cd026e755ff74926eab1986ad39bce2bdb9264d6c0a62835e991459840e22e57191f",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6e755f,758c41,...)))}",
"address": "9fMi2dxQmgXXhJfWbCQBBd8ZkDrx1ws9VzVrxKyKvc1TxyvkGiC",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "42207ca4b198e8f51852622b272e1f5fb183b84b10d95ee141c5cb85d8496f28",
"mainChain": true
},
{
"boxId": "8632bdb90bc53984f1ada543007d6049aa5914959dd301115619873c472e7602",
"transactionId": "d3a78b509d567ada2da31feff30913c613aff3d4fb7835f9bcef19d58681b361",
"blockId": "cbc2e571e3ed5cef7b9705542d56d739ebeb21ac7eecec02b43343c6e936568b",
"value": 1000000,
"index": 3,
"globalIndex": 43744868,
"creationHeight": 1391774,
"settlementHeight": 1391777,
"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": "c1a731d3738ec15c59a42a012378fa0b14fd81afd783b38c9037a5bab7b3266d",
"mainChain": true
},
{
"boxId": "2c7536ad6b563549d8cbf13db6df5cf2665b91680f3d34548f451b8476e8fc7a",
"transactionId": "d3a78b509d567ada2da31feff30913c613aff3d4fb7835f9bcef19d58681b361",
"blockId": "cbc2e571e3ed5cef7b9705542d56d739ebeb21ac7eecec02b43343c6e936568b",
"value": 4926899636,
"index": 4,
"globalIndex": 43744869,
"creationHeight": 1391774,
"settlementHeight": 1391777,
"ergoTree": "0008cd037c84abab2871332cb64b0646addf107a8d25a823f69c64b993ef6943367ac717",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(7c84ab,a45399,...)))}",
"address": "9hQeLqfkbNESaU1QfuaDENAL8Cdv6k9BgYA9MZwa2Nqhz4zxnhp",
"assets": [
{
"tokenId": "9944ff273ff169f32b851b96bbecdbb67f223101c15ae143de82b3e7f75b19d2",
"index": 0,
"amount": 58976,
"name": "GluonW GAUC",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "abaf9df62c6810b0198333b122d130c29d76d64c6d7f4d57108afc5aaa95efb5",
"index": 1,
"amount": 1487293614,
"name": "AirdropTest",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "22342ca384aa15022c311d0f46835c6df1d6df2f2e68a03f0e1e5952a4447939",
"index": 2,
"amount": 1,
"name": "The Djed Stablecoin Protocol Explained in a Single Image ",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 3,
"amount": 424150,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "af1a2e8005f6ffc9e291e121d1fb08795c5a079409b8ca56e20eb2f4f6f8553b",
"index": 4,
"amount": 4200000000,
"name": "🐶",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "886b7721bef42f60c6317d37d8752da8aca01898cae7dae61808c4a14225edc8",
"index": 5,
"amount": 308852,
"name": "GluonW GAU",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "aa900ea0696f5c3899e8643b2c81f254e55974f4f9c1c7730237d752346e91ab",
"mainChain": true
}
],
"size": 3832,
"isUnconfirmed": false
}