Transaction
ID: 78ea6e7ad6...c1ac
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002999999 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.143 ERG
Tokens:
99,999.64
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002999999 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0005 ERG
Tokens:
0
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0015 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.141 ERG
Tokens:
99,999.63
Transaction Details
Confirmations: 728,765
Total coins transferred: 0.146999999 ERG
Fees: 0.0015 ERG
Fees per byte: 0.000000161 ERG
Raw Transaction Data
{
"id": "78ea6e7ad674fa9ec703ea080dccdd6306f66d5e86e4cb5e28c0c9ca41d5c1ac",
"blockId": "fbd00ab86ce5853dc4b28ed20c78d7136fc3d55280f435fca06091f3770b2ff1",
"inclusionHeight": 1029810,
"timestamp": 1687263142359,
"index": 2,
"globalIndex": 5408263,
"numConfirmations": 728765,
"inputs": [
{
"boxId": "92a60180e2d5a244673ced936e245c96646ba0c7f25264e4f6fac90ce367ce2e",
"value": 2999999,
"index": 0,
"spendingProof": null,
"outputBlockId": "9b28727283b7a17320166f5081d6e703ea102ccb3e60ac0f6113e406380f255a",
"outputTransactionId": "bf0dec7cabebb9016cb225b6f7582efaacf089548d2d086aa17637bd8e9fafe5",
"outputIndex": 0,
"outputGlobalIndex": 30229133,
"outputCreatedAt": 1029802,
"outputSettledAt": 1029804,
"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(-30,107,-25,49,-44,-20,-63,15,-58,-46,67,75,-20,45,-55,-44,36,87,39,55,86,-62,-87,-111,59,118,-38,-53,-85,15,95,-16)\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": "26f11cf7a5fa7faea37341ce8e0a1de0b82e100b6835707504ee0575996aa8dd",
"index": 0,
"amount": 1,
"name": "Paideia Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f60fb5aa6127d4a2b537a91518a15eab1d21099cd34bc2e4c9f59022c3dd5af2",
"index": 1,
"amount": 1000282620776,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "110780a89bdd9b6284d2a7c2160400000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1687348800000,3022320770,2,0,0,0,0]"
},
"R6": {
"serializedValue": "1d05028c8084bd1484d2a7c216020000020000021414021414",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[2748350470,3022320770],[0,0],[0,0],[10,10],[10,10]]"
},
"R8": {
"serializedValue": "1d0202a0cda385020002a0cda3850200",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[273970000,0],[273970000,0]]"
},
"R7": {
"serializedValue": "0c3c646402e08612abee254962ae925d1874761239c9fa7b8fb21e3e03d819848fc2ccdd3d020720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720003d0eaa2172afc2d4a8297775f720fbca3c56577aae30560997504983d008d1a4020720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c64023d0eaa2172afc2d4a8297775f720fbca3c56577aae30560997504983d008d1a4020720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "da6a97fa554faaeecbf74f2cafc8ce7d97a91e3b3b954a292d970baf7bd8afdd",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "1130af2cdce003b940ed332cd0694eb0621cbe48ee54fbd6b513dd30820a90e8",
"outputTransactionId": "e6ad0c90a1f5f87786ab37e7703c8752d7b3c56c5a6c294ab6e3b49e72df6ccb",
"outputIndex": 1,
"outputGlobalIndex": 30198923,
"outputCreatedAt": 1029090,
"outputSettledAt": 1029092,
"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: 0\n53: 8\n54: 8\n55: 8\n56: CBigInt(0)\n57: true\n58: 0\n59: 0\n60: 1\n61: 1\n62: 1\n63: 0\n64: Coll(-30,107,-25,49,-44,-20,-63,15,-58,-46,67,75,-20,45,-55,-44,36,87,39,55,86,-62,-87,-111,59,118,-38,-53,-85,15,95,-16)\n65: 0\n66: 0\n67: 6\n68: 38\n69: 0\n70: 0\n71: 0\n72: 0\n73: 0\n74: 0\n75: 1\n76: 0\n77: 0\n78: 0\n79: 0\n80: 0\n81: 0\n82: CBigInt(0)\n83: 0\n84: 1\n85: 8\n86: 16\n87: 0\n88: 0\n89: 1\n90: 1\n91: 33\n92: 1\n93: 1\n94: 0\n95: 0\n96: 2\n97: 2\n98: 10\n99: 78\n100: -58\n101: 31\n102: 72\n103: 91\n104: -104\n105: -21\n106: -121\n107: 21\n108: 63\n109: 124\n110: 87\n111: -37\n112: 79\n113: 94\n114: -51\n115: 117\n116: 85\n117: 111\n118: -35\n119: -68\n120: 64\n121: 59\n122: 65\n123: -84\n124: -8\n125: 68\n126: 31\n127: -34\n128: -114\n129: 22\n130: 9\n131: 0",
"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[Coll[Long]]].get\n val coll37 = coll36(placeholder[Int](52))\n val coll38 = coll5.map({(tuple38: (Coll[Byte], Coll[Byte])) => coll15.map({(i40: Int) =>\n val i42 = i40 * placeholder[Int](53) + placeholder[Int](54)\n byteArrayToLong(tuple38._2.slice(i42, i42 + placeholder[Int](55)))\n }) })\n val tuple39 = (coll37.map({(l39: Long) => placeholder[BigInt](56) }), placeholder[Boolean](57))\n val box40 = OUTPUTS(placeholder[Int](58))\n val coll41 = box40.R5[Coll[Long]].get\n val coll42 = box40.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple43 = coll42(placeholder[Int](59))\n val coll44 = tuple43._1.digest\n val coll45 = box40.R4[Coll[AvlTree]].get\n val box46 = OUTPUTS(placeholder[Int](60))\n val bool47 = tuple43._2 == avlTree34\n val bool48 = coll42.slice(placeholder[Int](61), coll42.size) == coll17.slice(placeholder[Int](62), coll17.size)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](63))._1 == placeholder[Coll[Byte]](64), coll3(placeholder[Int](65))._1 == coll4(placeholder[Int](66)).get.slice(\n placeholder[Int](67), placeholder[Int](68)\n ), allOf(coll7.map({(i49: Int) =>\n val coll51 = coll16(i49)\n if (coll51(placeholder[Int](69)) >= placeholder[Long](70)) {(\n val coll52 = coll37.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll20(i49).toBigInt * bi54 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](71)) { coll35(i49)._1.toBigInt * bi54 / l23.toBigInt * coll24(placeholder[Int](72)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](73)) { coll35(i49)._2.toBigInt * bi54 / l26.toBigInt * coll27(placeholder[Int](74)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll38(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple39 }._2\n })), coll10(placeholder[Int](75)).toBigInt + coll7.map({(i49: Int) =>\n val coll51 = coll16(i49)\n if (coll51(placeholder[Int](76)) >= placeholder[Long](77)) {(\n val coll52 = coll37.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll20(i49).toBigInt * bi54 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](78)) { coll35(i49)._1.toBigInt * bi54 / l23.toBigInt * coll24(placeholder[Int](79)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](80)) { coll35(i49)._2.toBigInt * bi54 / l26.toBigInt * coll27(placeholder[Int](81)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll38(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple39 }\n }).fold(placeholder[BigInt](82), {(tuple49: (BigInt, (Coll[BigInt], Boolean))) => tuple49._1 + tuple49._2._1(placeholder[Int](83)) }) == coll41(\n placeholder[Int](84)\n ).toBigInt, avlTree19.remove(coll6, getVar[Coll[Byte]](4.toByte).get).get.digest == coll44, avlTree9.update(\n coll5.filter(\n {(tuple49: (Coll[Byte], Coll[Byte])) => byteArrayToLong(tuple49._2.slice(placeholder[Int](85), placeholder[Int](86))) > placeholder[Long](87) }\n ), getVar[Coll[Byte]](6.toByte).get\n ).get.digest == coll45(placeholder[Int](88)).digest, allOf(\n Coll[Boolean](\n blake2b256(box46.propositionBytes) == coll4(placeholder[Int](89)).get.slice(placeholder[Int](90), placeholder[Int](91)), box46.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n box40.value == box2.value, box40.tokens == coll3, coll45(placeholder[Int](92)).digest == coll8(placeholder[Int](93)).digest, bool47, bool48, coll41(\n placeholder[Int](94)\n ) == coll10(placeholder[Int](95)), coll41.slice(placeholder[Int](96), coll41.size) == coll10.slice(placeholder[Int](97), i11), box40.R6[\n Coll[Coll[Long]]\n ].get == coll21, bool48, bool47, box40.R8[Coll[Coll[Long]]].get == coll36\n )\n ), (coll5.size >= placeholder[Int](98)) || (\n coll44 == Coll[Byte](\n placeholder[Byte](99), placeholder[Byte](100), placeholder[Byte](101), placeholder[Byte](102), placeholder[Byte](103), placeholder[Byte](\n 104\n ), placeholder[Byte](105), placeholder[Byte](106), placeholder[Byte](107), placeholder[Byte](108), placeholder[Byte](109), placeholder[Byte](\n 110\n ), placeholder[Byte](111), placeholder[Byte](112), placeholder[Byte](113), placeholder[Byte](114), placeholder[Byte](115), placeholder[Byte](\n 116\n ), placeholder[Byte](117), placeholder[Byte](118), placeholder[Byte](119), placeholder[Byte](120), placeholder[Byte](121), placeholder[Byte](\n 122\n ), placeholder[Byte](123), placeholder[Byte](124), placeholder[Byte](125), placeholder[Byte](126), placeholder[Byte](127), placeholder[Byte](\n 128\n ), placeholder[Byte](129), placeholder[Byte](130), placeholder[Byte](131)\n )\n )\n )\n )\n )\n}",
"address": "st4bkDp4da9YPXFokFtkXxL1MNDD8mzfKQA83pXqp7wnc1v5XHEYZ2LHoJVMGMqiP2myCSGu9cAgF1BANxSApN6zeiKrs7zuugEB9BUe6Cx2xSZeXYX4f2TgpP8Qpo4uAoirZUp1xQrbdrh7wLjjE3KPHfsPrFuV7Gg2ydUETMJe7mo6irmDwjZXinxvzgbsXysFjYmrrzLsAbsCx9BwExXnNhQJoLvpN8TA8hTmyU7qDVMKGodXfBRaiRJD9imv7K9cYHjGXtXidveZH43E9UGiAgXDwViRy8kCazK9L4rCqiNXVAtuowpUtmvTNMCfUrBy6Mf2sY1n4PC23pWJ4Hei8C23C2rJtztrZLxFTAQ6hyhaedhUBfZrbx3BpDzUu9WPrDNZxVerxQ1GThTc3KPKhDN7LBKeMcGF6JimPxBiAtCzujMAaQWke9RRCENvoWuW7NgZeTjcR6gvdZnaiNWALtXiXoDyeuFdQdY24JkULcnUh3bvVnVeHaRQd21SMNhYKNYEXwm7dbtHeomZ386Frc1zFHYfhLCKoyxhAAF7ysntyLwm2PMPGAMkBpamkpFXsBZsWhJn42u5Pnf157upcJweLyUtkLN28xTmQgQnRsN3knw89NswragVco278TX7BS2JrA2jDmEvyBE4Sr6RzYnFVgJbva2o1rs9bY1uAcWCkKjmRCxEkjQ1EBtD32dMoAteoSaV9pWHxU5aDs7jvmLJXh2NXLXCQjHXfNBimd8pBPm6jDfQUZLibpPssYWLNwi915o5VxvgyciuD1DpPLaMeToFVUHFqaoR8dTdttMYKkshrfYQxQsWdnQDWGEFsCe71uw7TgoMAj7rbKKS1po5z3fUcXJ7msGGjxjdQ7KDbbTziXVFa8AF3PM2MdQ4uibvQMqTTMc3fgac2YwTyxtddkRwbNstGe88rd8EfYAmmvuWTucmjEFSwASqMG94yUvXtRwbTLzUqoGuUdt5hsLHHJgXipuojzz7G2tsRRwZcTBkqbaDMLK9vqDXWPRe4vE92B28ojtxHPTPNZx3mfvHC2ATZVResKoLR4dYEKTuzmEXwZqtarN4nLVfPg5eGEdcezxii1pNjocvGg5xdiNwpe8eWSHwomZR6dBe7AfX8Gfjz8FhQWKMehAVvSUCDAtWyBtKEb46u4JpSfdZuwNcM3pDvDgS1wy9Xrsfg9ceWMYjadnN5jdBwN7vqkxNZgaQokuxzEKAf1MQEt9mRFztkZeh7W7eg3UjRz76xa43NsuzEZHxvNdy6dTqC8A7gbwigEXgdXdciSepDz8TYwSHumENyrQ4yQYAynr3fUSTuuPyVapFUCG6N7KDjSnnEbvWZJ9zVV7pZdMDo2hjaAX9zDABWbogkneHXhDkXxjSRTPP5vt4H6EZw7vf8R34W4naG4tS51hpLqvKQEFvnWPi3PnSoeeca9oZYz1q22Jgf7m732Er8wxjeWTYAyBNXxBnediBxjQhh4F7CCYXv44j1hsAX5NTFQJAsG1wcvxUjKvaugePTqDWwGt1RyJoYxfFrMrFxXGwUNjEWVaDRJ868XMfpmr25bgPFisHBNa9CmNQRQfH1ifdb2dSQQdB8oG3hrgBBxGhoXYCLWVrNhwbTNdPiNZsaqXHQmVbAVRPyaLerJSLT8wjXd2Drp87uoYp1HoJyRSJTgGjRsBot8jtwDNu5f9HVXdDL69qcUTpDrKrBEzc7xAFgmg8z2WVttsstNNyjSxLa8dHXt8Se2ogQngjnVi4uBBHgrWShvE9t7hm4eQSrYQWoC2YmKKp6pRGaScrNGnqwdkrrZi4ezqZKgmUr3Av4twjWdLzohBPkTrS6fo6oWSSvY4qKRZPGGHozQkg5VSB5QjrrrhVpyyX9ghL4829AHp1juvVKqTt4ZAZ8JhJ2CRRiMLSS91L8etXynkWajaDVnLtyfgXUiXmkX4ZHrj291Tv3vRPgXCoqjhTqNxcfNH6BvyLGQcCb63aoLsQbeCq8FiyaZRS7dce4qjT72XUvfN5qod8tAB4oAG6wUmnA3XaodbN77Efg9gzZSSHXJzjw6YeGvGpZG2QG86kNGGLMkHjhQSSRQEctbPK84kQ7LLYGTFCZwDZdqLPUptF9ommPCpW62kG8i2WM1i8uHdokgjYn14AbEBkJw7mFBnPedPmSeJWdCGMdQ8WhJXvt1BdPhhyaMRzhqEgjazfVQuCcio9uZd1y2CsbjcrJkKkvWmfXrxJ5MaeLBRxn19hv8GERVeAsdQauVVkeShpfLUCmwCPMB5GomHhK5UF8Ggp78bRA3MB5N1xzUrnGyNxNp5xRu3SCEzvVujXL45tYYXfWaZJAiC2oLiHFzbJWSehcseie82LcG43tnomhKMC34wsY3kHhvBw84z5snJPL8HgJDs6yK9Qz8v6A7CkNbi3MtcxtqE9MM9Z9tU1Bm7tzA6ajX4FrxFtb8v9ktwdGtYiNbJzzTxRasPnH2gyuBFk8v9mRC",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "feb5d26e289784fc4ed20ce32f3e65fe1abeb5cf3a100a1c4aeb6d7bee56c541",
"value": 143000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "9b28727283b7a17320166f5081d6e703ea102ccb3e60ac0f6113e406380f255a",
"outputTransactionId": "bf0dec7cabebb9016cb225b6f7582efaacf089548d2d086aa17637bd8e9fafe5",
"outputIndex": 5,
"outputGlobalIndex": 30229138,
"outputCreatedAt": 1029802,
"outputSettledAt": 1029804,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(2,-40,-48,84,-100,-23,-57,-23,83,100,-108,-5,3,-40,117,-105,75,-124,84,20,-25,-69,81,29,36,23,-125,112,-86,1,-53,-67)\n3: false\n4: Coll(-10,15,-75,-86,97,39,-44,-94,-75,55,-87,21,24,-95,94,-85,29,33,9,-100,-45,75,-62,-28,-55,-11,-112,34,-61,-35,90,-14)\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": "f60fb5aa6127d4a2b537a91518a15eab1d21099cd34bc2e4c9f59022c3dd5af2",
"index": 0,
"amount": 999996444,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "fc06fc51fdda47073e495fd29b7e5e18207619847655523d7add87aa165b50ab",
"value": 1000000,
"index": 0,
"outputBlockId": "5cbf946d98bfa92e50063d107e53cf67a07c969179301a07b14a9dc236b11a66",
"outputTransactionId": "ef247973c6fc7ffd367fd30e6ad987b19e64f157f04e28eb5fedd6fc3ad4f594",
"outputIndex": 2,
"ergoTree": "100904000e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020442040004000e2002d8d0549ce9c7e9536494fb03d875974b845414e7bb511d24178370aa01cbbd0100d801d601b2a5730000d19683040193db6308a7db6308720190c1a7c1720193cbc27201b4e4b2dc640be4c6720104640283010e7301e4e3000e73020073037304aea4d9010263d801d604db630872029591b172047305938cb272047306000173077308",
"address": "FDdVv3XcPnh67Hm9GfPJpFCLuVeaYKY9MGf67RZfgNcGhsxDZPTz5JVn86hKGoSf3aCbfDgNYY6o7gwdaX7aeWexWM5rknVRf73HuT7oVn7irkt4uePVAKHmvztiTfDV2Vtg3pYLBB9jguWqSBH47SAfztDaARw6fFvmsSBzNyPaByqhJrvUwgBSppAY2KJzEzmkdsrBJeX6HhL4e967mLqDxmkb8FqwsoZ9WZYA8FJN9N7i5fN8pa4T1Rb8hMbJ",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "641459472d3a27b591340084aa5b9da07522a6e36eef16005fd850a3e9bbc38d8d07072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "89012f72e0f09d352b1766253a14235c1eacf87baae53a9475eab1526ca3fa7c",
"transactionId": "78ea6e7ad674fa9ec703ea080dccdd6306f66d5e86e4cb5e28c0c9ca41d5c1ac",
"blockId": "fbd00ab86ce5853dc4b28ed20c78d7136fc3d55280f435fca06091f3770b2ff1",
"value": 2999999,
"index": 0,
"globalIndex": 30229370,
"creationHeight": 1029808,
"settlementHeight": 1029810,
"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(-30,107,-25,49,-44,-20,-63,15,-58,-46,67,75,-20,45,-55,-44,36,87,39,55,86,-62,-87,-111,59,118,-38,-53,-85,15,95,-16)\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": "26f11cf7a5fa7faea37341ce8e0a1de0b82e100b6835707504ee0575996aa8dd",
"index": 0,
"amount": 1,
"name": "Paideia Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f60fb5aa6127d4a2b537a91518a15eab1d21099cd34bc2e4c9f59022c3dd5af2",
"index": 1,
"amount": 1000282620776,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "110780a89bdd9b62a29fcbc7180400000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1687348800000,3296290769,2,0,0,0,0]"
},
"R6": {
"serializedValue": "1d05028c8084bd1484d2a7c216020000020000021414021414",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[2748350470,3022320770],[0,0],[0,0],[10,10],[10,10]]"
},
"R8": {
"serializedValue": "1d0202a0cda385020002a0cda3850200",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[273970000,0],[273970000,0]]"
},
"R7": {
"serializedValue": "0c3c6464024ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720003d0eaa2172afc2d4a8297775f720fbca3c56577aae30560997504983d008d1a4020720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c6402c7bb1b37c6d66700a1989aebd136dc3982b0f16ab824822b150b7de6b0d44275020720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "3e55e1f11b9d5630d3296263d9745db9b0ab245462008e92b284e3c2815d6494",
"mainChain": true
},
{
"boxId": "957c37a89aecc5fb31d21014cdee7fcada87561e61ae5842e5bfe569bc9c80af",
"transactionId": "78ea6e7ad674fa9ec703ea080dccdd6306f66d5e86e4cb5e28c0c9ca41d5c1ac",
"blockId": "fbd00ab86ce5853dc4b28ed20c78d7136fc3d55280f435fca06091f3770b2ff1",
"value": 1000000,
"index": 1,
"globalIndex": 30229371,
"creationHeight": 1029808,
"settlementHeight": 1029810,
"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: 0\n53: 8\n54: 8\n55: 8\n56: CBigInt(0)\n57: true\n58: 0\n59: 0\n60: 1\n61: 1\n62: 1\n63: 0\n64: Coll(-30,107,-25,49,-44,-20,-63,15,-58,-46,67,75,-20,45,-55,-44,36,87,39,55,86,-62,-87,-111,59,118,-38,-53,-85,15,95,-16)\n65: 0\n66: 0\n67: 6\n68: 38\n69: 0\n70: 0\n71: 0\n72: 0\n73: 0\n74: 0\n75: 1\n76: 0\n77: 0\n78: 0\n79: 0\n80: 0\n81: 0\n82: CBigInt(0)\n83: 0\n84: 1\n85: 8\n86: 16\n87: 0\n88: 0\n89: 1\n90: 1\n91: 33\n92: 1\n93: 1\n94: 0\n95: 0\n96: 2\n97: 2\n98: 10\n99: 78\n100: -58\n101: 31\n102: 72\n103: 91\n104: -104\n105: -21\n106: -121\n107: 21\n108: 63\n109: 124\n110: 87\n111: -37\n112: 79\n113: 94\n114: -51\n115: 117\n116: 85\n117: 111\n118: -35\n119: -68\n120: 64\n121: 59\n122: 65\n123: -84\n124: -8\n125: 68\n126: 31\n127: -34\n128: -114\n129: 22\n130: 9\n131: 0",
"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[Coll[Long]]].get\n val coll37 = coll36(placeholder[Int](52))\n val coll38 = coll5.map({(tuple38: (Coll[Byte], Coll[Byte])) => coll15.map({(i40: Int) =>\n val i42 = i40 * placeholder[Int](53) + placeholder[Int](54)\n byteArrayToLong(tuple38._2.slice(i42, i42 + placeholder[Int](55)))\n }) })\n val tuple39 = (coll37.map({(l39: Long) => placeholder[BigInt](56) }), placeholder[Boolean](57))\n val box40 = OUTPUTS(placeholder[Int](58))\n val coll41 = box40.R5[Coll[Long]].get\n val coll42 = box40.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple43 = coll42(placeholder[Int](59))\n val coll44 = tuple43._1.digest\n val coll45 = box40.R4[Coll[AvlTree]].get\n val box46 = OUTPUTS(placeholder[Int](60))\n val bool47 = tuple43._2 == avlTree34\n val bool48 = coll42.slice(placeholder[Int](61), coll42.size) == coll17.slice(placeholder[Int](62), coll17.size)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](63))._1 == placeholder[Coll[Byte]](64), coll3(placeholder[Int](65))._1 == coll4(placeholder[Int](66)).get.slice(\n placeholder[Int](67), placeholder[Int](68)\n ), allOf(coll7.map({(i49: Int) =>\n val coll51 = coll16(i49)\n if (coll51(placeholder[Int](69)) >= placeholder[Long](70)) {(\n val coll52 = coll37.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll20(i49).toBigInt * bi54 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](71)) { coll35(i49)._1.toBigInt * bi54 / l23.toBigInt * coll24(placeholder[Int](72)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](73)) { coll35(i49)._2.toBigInt * bi54 / l26.toBigInt * coll27(placeholder[Int](74)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll38(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple39 }._2\n })), coll10(placeholder[Int](75)).toBigInt + coll7.map({(i49: Int) =>\n val coll51 = coll16(i49)\n if (coll51(placeholder[Int](76)) >= placeholder[Long](77)) {(\n val coll52 = coll37.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll20(i49).toBigInt * bi54 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](78)) { coll35(i49)._1.toBigInt * bi54 / l23.toBigInt * coll24(placeholder[Int](79)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](80)) { coll35(i49)._2.toBigInt * bi54 / l26.toBigInt * coll27(placeholder[Int](81)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll38(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple39 }\n }).fold(placeholder[BigInt](82), {(tuple49: (BigInt, (Coll[BigInt], Boolean))) => tuple49._1 + tuple49._2._1(placeholder[Int](83)) }) == coll41(\n placeholder[Int](84)\n ).toBigInt, avlTree19.remove(coll6, getVar[Coll[Byte]](4.toByte).get).get.digest == coll44, avlTree9.update(\n coll5.filter(\n {(tuple49: (Coll[Byte], Coll[Byte])) => byteArrayToLong(tuple49._2.slice(placeholder[Int](85), placeholder[Int](86))) > placeholder[Long](87) }\n ), getVar[Coll[Byte]](6.toByte).get\n ).get.digest == coll45(placeholder[Int](88)).digest, allOf(\n Coll[Boolean](\n blake2b256(box46.propositionBytes) == coll4(placeholder[Int](89)).get.slice(placeholder[Int](90), placeholder[Int](91)), box46.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n box40.value == box2.value, box40.tokens == coll3, coll45(placeholder[Int](92)).digest == coll8(placeholder[Int](93)).digest, bool47, bool48, coll41(\n placeholder[Int](94)\n ) == coll10(placeholder[Int](95)), coll41.slice(placeholder[Int](96), coll41.size) == coll10.slice(placeholder[Int](97), i11), box40.R6[\n Coll[Coll[Long]]\n ].get == coll21, bool48, bool47, box40.R8[Coll[Coll[Long]]].get == coll36\n )\n ), (coll5.size >= placeholder[Int](98)) || (\n coll44 == Coll[Byte](\n placeholder[Byte](99), placeholder[Byte](100), placeholder[Byte](101), placeholder[Byte](102), placeholder[Byte](103), placeholder[Byte](\n 104\n ), placeholder[Byte](105), placeholder[Byte](106), placeholder[Byte](107), placeholder[Byte](108), placeholder[Byte](109), placeholder[Byte](\n 110\n ), placeholder[Byte](111), placeholder[Byte](112), placeholder[Byte](113), placeholder[Byte](114), placeholder[Byte](115), placeholder[Byte](\n 116\n ), placeholder[Byte](117), placeholder[Byte](118), placeholder[Byte](119), placeholder[Byte](120), placeholder[Byte](121), placeholder[Byte](\n 122\n ), placeholder[Byte](123), placeholder[Byte](124), placeholder[Byte](125), placeholder[Byte](126), placeholder[Byte](127), placeholder[Byte](\n 128\n ), placeholder[Byte](129), placeholder[Byte](130), placeholder[Byte](131)\n )\n )\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "f8e258d0114b0e371c65dede35bd800909f2ff20468dfa9ca7af04dc2cb21381",
"mainChain": true
},
{
"boxId": "896ceda13b5da833b53d73e99527c9e05a88b4fba2a4c98cdbfc601ea8269aea",
"transactionId": "78ea6e7ad674fa9ec703ea080dccdd6306f66d5e86e4cb5e28c0c9ca41d5c1ac",
"blockId": "fbd00ab86ce5853dc4b28ed20c78d7136fc3d55280f435fca06091f3770b2ff1",
"value": 500000,
"index": 2,
"globalIndex": 30229372,
"creationHeight": 1029808,
"settlementHeight": 1029810,
"ergoTree": "0008cd03553448c194fdd843c87d080f5e8ed983f5bb2807b13b45a9683bba8c7bfb5ae8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(553448,8bebb3,...)))}",
"address": "9h7L7sUHZk43VQC3PHtSp5ujAWcZtYmWATBH746wi75C5XHi68b",
"assets": [
{
"tokenId": "f60fb5aa6127d4a2b537a91518a15eab1d21099cd34bc2e4c9f59022c3dd5af2",
"index": 0,
"amount": 100,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "8614f258ea1aee3def75d3e13d49d1fde3588c094faa7d04da3d7001123241d1",
"mainChain": true
},
{
"boxId": "523b1d8eb96ed42cf53203db8b0de919c766e37322827861926c7836e24dcefd",
"transactionId": "78ea6e7ad674fa9ec703ea080dccdd6306f66d5e86e4cb5e28c0c9ca41d5c1ac",
"blockId": "fbd00ab86ce5853dc4b28ed20c78d7136fc3d55280f435fca06091f3770b2ff1",
"value": 1500000,
"index": 3,
"globalIndex": 30229373,
"creationHeight": 1029808,
"settlementHeight": 1029810,
"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": "5dd68d478c1c26c8dbd50885774598a688424faa75e207e8629671319809dbba",
"mainChain": true
},
{
"boxId": "6277adfa88e08891bc4616139c47dfbeeede4dd8edac040e6e888a9ba8893d1f",
"transactionId": "78ea6e7ad674fa9ec703ea080dccdd6306f66d5e86e4cb5e28c0c9ca41d5c1ac",
"blockId": "fbd00ab86ce5853dc4b28ed20c78d7136fc3d55280f435fca06091f3770b2ff1",
"value": 141000000,
"index": 4,
"globalIndex": 30229374,
"creationHeight": 1029808,
"settlementHeight": 1029810,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(2,-40,-48,84,-100,-23,-57,-23,83,100,-108,-5,3,-40,117,-105,75,-124,84,20,-25,-69,81,29,36,23,-125,112,-86,1,-53,-67)\n3: false\n4: Coll(-10,15,-75,-86,97,39,-44,-94,-75,55,-87,21,24,-95,94,-85,29,33,9,-100,-45,75,-62,-28,-55,-11,-112,34,-61,-35,90,-14)\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": "f60fb5aa6127d4a2b537a91518a15eab1d21099cd34bc2e4c9f59022c3dd5af2",
"index": 0,
"amount": 999996344,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "5097d56c9270c7a2b4913e65285366e633dc8ba3859146877ecd40189c293376",
"mainChain": true
}
],
"size": 9326,
"isUnconfirmed": false
}