Transaction
ID: 2ff2810ecd...baee
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
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.9257 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
0
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.9256 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 197,381
Total coins transferred: 0.9277 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000002079 ERG
Raw Transaction Data
{
"id": "2ff2810ecd7292a53ae5fb5cff33d5677cc7ea846cdde7d64ebcdc7e352ebaee",
"blockId": "10902cd0ceb38bf4f88ea90deb0370698accfb56f76337886f81b08c6368d625",
"inclusionHeight": 1560670,
"timestamp": 1751571385618,
"index": 4,
"globalIndex": 9165936,
"numConfirmations": 197381,
"inputs": [
{
"boxId": "828ecb17ce88aecf1c566d3526b4ca39d96c3d88301f3b5280d3f599f23e6fe1",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "9bac6ae3d581f7928a0ea63c87519de60fa07c08dde0d7aa007ae4cde5d23a2f",
"outputTransactionId": "b2db773e99ba83dd94ad49d83d480feea4d7aa78242ee2dffb0df27742765122",
"outputIndex": 0,
"outputGlobalIndex": 48700443,
"outputCreatedAt": 1560668,
"outputSettledAt": 1560669,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-120,-12,67,-5,-13,94,-47,42,116,16,-94,2,35,-26,118,-76,104,-61,1,-92,-8,78,3,82,91,19,101,55,108,-121,-40,58)\n1: SigmaProp(ProveDlog(ECPoint(75acc4,25ee17,...)))\n2: 0\n3: 0\n4: 1\n5: 127\n6: 3\n7: 2\n8: 0\n9: 1\n10: Coll(0,8,-51,2,18,-119,25,-122,77,69,118,50,84,63,54,-89,67,122,-126,85,-111,83,86,57,-80,19,-28,1,-39,4,63,83,-32,-125,-69,-113)\n11: 720\n12: 30\n13: 720\n14: 30\n15: 0\n16: 0\n17: 30\n18: 8\n19: 1\n20: 1\n21: 0\n22: 1\n23: 1\n24: true\n25: false\n26: 0\n27: 10\n28: 100\n29: 0\n30: 1\n31: 2\n32: 1\n33: 0\n34: 1\n35: 0\n36: 2\n37: 2\n38: 0\n39: 60\n40: 0\n41: 3\n42: 1\n43: 0\n44: 2\n45: 1\n46: 2\n47: 2\n48: 0\n49: 0\n50: false\n51: 0\n52: 0\n53: false\n54: 0\n55: true\n56: 4\n57: 1\n58: 0\n59: 0\n60: 5\n61: 1\n62: 0\n63: 0\n64: 800\n65: 1000\n66: 1\n67: 120\n68: 1000\n69: 0\n70: 2\n71: 30\n72: 1000\n73: 0\n74: 3\n75: 2\n76: 1\n77: 0\n78: 0\n79: true\n80: 0\n81: true\n82: 6\n83: 0\n84: 1\n85: 0\n86: 1\n87: 7\n88: 0\n89: 0\n90: 2\n91: 1\n92: 0\n93: 1\n94: 8\n95: 1\n96: 120\n97: 1000\n98: 0\n99: 2\n100: 30\n101: 1000\n102: 0\n103: 3\n104: 2\n105: 1\n106: 0\n107: 1\n108: 0\n109: true\n110: 0\n111: true\n112: 800\n113: 1000\n114: 9\n115: 0\n116: 0\n117: 1\n118: 0\n119: 1\n120: false",
"ergoTreeScript": "{\n val i1 = getVar[Int](0.toByte).get\n val func2 = {(box2: Box) => box2.tokens.exists({(tuple4: (Coll[Byte], Long)) => tuple4._1 == placeholder[Coll[Byte]](0) }) }\n val prop3 = placeholder[SigmaProp](1)\n val func4 = {(tuple4: (SigmaProp, Box)) =>\n val coll6 = tuple4._2.propositionBytes\n val coll7 = tuple4._1.propBytes\n if (coll6(placeholder[Int](2)).toInt == placeholder[Int](3)) { coll6 == coll7 } else {(\n val i8 = coll6.size\n coll7.slice(placeholder[Int](4), coll7.size) == coll6.slice(if (i8 > placeholder[Int](5)) { placeholder[Int](6) } else { placeholder[Int](7) }, i8)\n )}\n }\n val l5 = SELF.R8[Long].get\n val coll6 = SELF.propositionBytes\n val coll7 = SELF.tokens\n val tuple8 = coll7(placeholder[Int](8))\n val coll9 = tuple8._1\n val tuple10 = coll7(placeholder[Int](9))\n val coll11 = tuple10._1\n val i12 = SELF.R4[Int].get\n val tuple13 = SELF.R5[(SigmaProp, SigmaProp)].get\n val prop14 = tuple13._1\n val tuple15 = SELF.R6[(Coll[Byte], Coll[Byte])].get\n val prop16 = tuple13._2\n val l17 = SELF.R9[Long].get\n val coll18 = placeholder[Coll[Byte]](10)\n val func19 = {(coll19: Coll[Byte]) =>\n OUTPUTS.forall(\n {(box21: Box) => allOf(Coll[Boolean](box21.tokens.forall({(tuple23: (Coll[Byte], Long)) => tuple23._1 != coll19 }), box21.propositionBytes != coll6)) }\n )\n }\n val tuple20 = SELF.R7[(Boolean, Boolean)].get\n val bool21 = tuple20._1\n val i22 = i12 - HEIGHT\n val bool23 = (i22 < placeholder[Int](11)) && (i22 >= placeholder[Int](12))\n val bool24 = (i22 >= placeholder[Int](13)) && (i22 >= placeholder[Int](14))\n val bool25 = tuple20._2\n val coll26 = tuple15._1\n val bool27 = coll26.size > placeholder[Int](15)\n val coll28 = tuple15._2\n val bool29 = coll28.size > placeholder[Int](16)\n val i30 = i12 + placeholder[Int](17)\n val i31 = i30 + placeholder[Int](18)\n if (i1 == placeholder[Int](19)) {(\n val box32 = INPUTS(placeholder[Int](20))\n val box33 = OUTPUTS(placeholder[Int](21))\n val tuple34 = box33.R5[(SigmaProp, SigmaProp)].get\n val prop35 = tuple34._2\n val l36 = box33.R9[Long].get\n val coll37 = box33.tokens\n val tuple38 = coll37(placeholder[Int](22))\n val box39 = OUTPUTS(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n func2(box32), allOf(\n Coll[Boolean](prop35 != prop3, func4((prop35, box32)), box33.R7[(Boolean, Boolean)].get == (placeholder[Boolean](24), placeholder[Boolean](25)))\n )\n )\n ), allOf(Coll[Boolean](l36 > placeholder[Long](26), l36 == placeholder[Long](27) * l5 / placeholder[Long](28), tuple38._2 == l5 + l36)), allOf(\n Coll[Boolean](\n box33.value == SELF.value, box33.propositionBytes == coll6, coll37(placeholder[Int](29)) == (\n coll9, placeholder[Long](30)\n ), tuple38._1 == coll11, box33.R4[Int].get == i12, tuple34._1 == prop14, box33.R6[(Coll[Byte], Coll[Byte])].get == tuple15, box33.R8[\n Long\n ].get == l5\n )\n ), allOf(Coll[Boolean](box39.propositionBytes == box32.propositionBytes, func2(box39)))\n )\n )\n )\n )} else { if (i1 == placeholder[Int](31)) {(\n val box32 = INPUTS(placeholder[Int](32))\n val box33 = OUTPUTS(placeholder[Int](33))\n val box34 = OUTPUTS(placeholder[Int](34))\n val tuple35 = box34.tokens(placeholder[Int](35))\n val l36 = l17 / placeholder[Long](36)\n val box37 = OUTPUTS(placeholder[Int](37))\n val tuple38 = box37.tokens(placeholder[Int](38))\n sigmaProp(allOf(Coll[Boolean](bool21, i22 >= placeholder[Int](39), allOf(Coll[Boolean](func4((prop16, box32)), func2(box32))), allOf(Coll[Boolean](func4((prop14, box33)), box33.tokens(placeholder[Int](40)) == (coll11, l5))), allOf(Coll[Boolean](box34.propositionBytes == box32.propositionBytes, allOf(Coll[Boolean](tuple35._1 == coll11, tuple35._2 == l36)), func2(box34))), allOf(Coll[Boolean](box37.propositionBytes == coll18, allOf(Coll[Boolean](tuple38._1 == coll11, tuple38._2 == tuple10._2 - l5 - l36)))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](41)) {(\n val box32 = INPUTS(placeholder[Int](42))\n val box33 = OUTPUTS(placeholder[Int](43))\n val l34 = l5 / placeholder[Long](44)\n val box35 = OUTPUTS(placeholder[Int](45))\n val l36 = l5 - l34\n val l37 = l36 / placeholder[Long](46)\n val box38 = OUTPUTS.getOrElse(placeholder[Int](47), SELF)\n sigmaProp(allOf(Coll[Boolean](bool21, func4((prop14, box32)), allOf(Coll[Boolean](box33.propositionBytes == box32.propositionBytes, if (bool24) { box33.tokens(placeholder[Int](48)) == (coll11, l5) } else { if (bool23) { box33.tokens(placeholder[Int](49)) == (coll11, l34) } else { placeholder[Boolean](50) } })), allOf(Coll[Boolean](func4((prop16, box35)), if (bool24) {(\n val tuple39 = box35.tokens(placeholder[Int](51))\n allOf(Coll[Boolean](tuple39._1 == coll11, tuple39._2 == l17))\n )} else { if (bool23) {(\n val tuple39 = box35.tokens(placeholder[Int](52))\n allOf(Coll[Boolean](tuple39._1 == coll11, tuple39._2 == l17 + l36 - l37))\n )} else { placeholder[Boolean](53) } })), if (bool23) {(\n val tuple39 = box38.tokens(placeholder[Int](54))\n allOf(Coll[Boolean](box38.propositionBytes == coll18, allOf(Coll[Boolean](tuple39._1 == coll11, tuple39._2 == l37))))\n )} else { placeholder[Boolean](55) }, func19(coll9))))\n )} else { if (i1 == placeholder[Int](56)) {(\n val box32 = INPUTS(placeholder[Int](57))\n val box33 = OUTPUTS(placeholder[Int](58))\n sigmaProp(allOf(Coll[Boolean](!bool21, func4((prop14, box32)), allOf(Coll[Boolean](box33.propositionBytes == box32.propositionBytes, box33.tokens(placeholder[Int](59)) == (coll11, l5))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](60)) {(\n val box32 = INPUTS(placeholder[Int](61))\n val box33 = OUTPUTS(placeholder[Int](62))\n val tuple34 = box33.tokens(placeholder[Int](63))\n val l35 = placeholder[Long](64) * l5 / placeholder[Long](65)\n val box36 = OUTPUTS.getOrElse(placeholder[Int](66), SELF)\n val l37 = if (bool27) { placeholder[Long](67) * l5 / placeholder[Long](68) } else { placeholder[Long](69) }\n val box38 = OUTPUTS.getOrElse(placeholder[Int](70), SELF)\n val l39 = if (bool29) { placeholder[Long](71) * l5 / placeholder[Long](72) } else { placeholder[Long](73) }\n val box40 = if (bool27 && bool29) { OUTPUTS(placeholder[Int](74)) } else { if (bool27) { OUTPUTS(placeholder[Int](75)) } else { OUTPUTS(placeholder[Int](76)) } }\n val tuple41 = box40.tokens(placeholder[Int](77))\n sigmaProp(allOf(Coll[Boolean](HEIGHT >= i30, HEIGHT >= i31, bool21, !bool25, allOf(Coll[Boolean](func4((prop16, box32)), func2(box32))), allOf(Coll[Boolean](box33.propositionBytes == box32.propositionBytes, allOf(Coll[Boolean](tuple34._1 == coll11, tuple34._2 == l17 + l35)), func2(box33))), if (bool27) {(\n val tuple42 = box36.tokens(placeholder[Int](78))\n allOf(Coll[Boolean](box36.propositionBytes == coll26, allOf(Coll[Boolean](tuple42._1 == coll11, tuple42._2 == l37))))\n )} else { placeholder[Boolean](79) }, if (bool29 && bool27) {(\n val tuple42 = box38.tokens(placeholder[Int](80))\n allOf(Coll[Boolean](box38.propositionBytes == coll28, allOf(Coll[Boolean](tuple42._1 == coll11, tuple42._2 == l39))))\n )} else { placeholder[Boolean](81) }, allOf(Coll[Boolean](box40.propositionBytes == coll18, allOf(Coll[Boolean](tuple41._1 == coll11, tuple41._2 == l5 - l35 + l37 + l39)))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](82)) {(\n val box32 = OUTPUTS(placeholder[Int](83))\n val tuple33 = box32.R7[(Boolean, Boolean)].get\n val coll34 = box32.tokens\n sigmaProp(allOf(Coll[Boolean]((HEIGHT >= i12) && bool21, HEIGHT < i31, func4((prop14, INPUTS(placeholder[Int](84)))), tuple33._2, allOf(Coll[Boolean](box32.value == SELF.value, box32.propositionBytes == coll6, coll34(placeholder[Int](85)) == tuple8, coll34(placeholder[Int](86)) == tuple10, box32.R4[Int].get == i12, box32.R5[(SigmaProp, SigmaProp)].get == tuple13, box32.R6[(Coll[Byte], Coll[Byte])].get == tuple15, tuple33._1 == bool21, box32.R8[Long].get == l5, box32.R9[Long].get == l17)))))\n )} else { if (i1 == placeholder[Int](87)) {(\n val box32 = OUTPUTS(placeholder[Int](88))\n val tuple33 = box32.tokens(placeholder[Int](89))\n val l34 = l17 / placeholder[Long](90)\n val box35 = OUTPUTS(placeholder[Int](91))\n val tuple36 = box35.tokens(placeholder[Int](92))\n sigmaProp(allOf(Coll[Boolean](bool25, func4((prop3, INPUTS(placeholder[Int](93)))), allOf(Coll[Boolean](func4((prop14, box32)), allOf(Coll[Boolean](tuple33._1 == coll11, tuple33._2 == l34 + l5)))), allOf(Coll[Boolean](box35.propositionBytes == coll18, allOf(Coll[Boolean](tuple36._1 == coll11, tuple36._2 == l17 - l34)))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](94)) {(\n val box32 = OUTPUTS.getOrElse(placeholder[Int](95), SELF)\n val l33 = if (bool27) { placeholder[Long](96) * l5 / placeholder[Long](97) } else { placeholder[Long](98) }\n val box34 = OUTPUTS.getOrElse(placeholder[Int](99), SELF)\n val l35 = if (bool29) { placeholder[Long](100) * l5 / placeholder[Long](101) } else { placeholder[Long](102) }\n val box36 = if (bool27 && bool29) { OUTPUTS(placeholder[Int](103)) } else { if (bool27) { OUTPUTS(placeholder[Int](104)) } else { OUTPUTS(placeholder[Int](105)) } }\n val tuple37 = box36.tokens(placeholder[Int](106))\n sigmaProp(allOf(Coll[Boolean](bool25, func4((prop3, INPUTS(placeholder[Int](107)))), if (bool27) {(\n val tuple38 = box32.tokens(placeholder[Int](108))\n allOf(Coll[Boolean](box32.propositionBytes == coll26, allOf(Coll[Boolean](tuple38._1 == coll11, tuple38._2 == l33))))\n )} else { placeholder[Boolean](109) }, if (bool29 && bool27) {(\n val tuple38 = box34.tokens(placeholder[Int](110))\n allOf(Coll[Boolean](box34.propositionBytes == coll28, allOf(Coll[Boolean](tuple38._1 == coll11, tuple38._2 == l35))))\n )} else { placeholder[Boolean](111) }, allOf(Coll[Boolean](box36.propositionBytes == coll18, allOf(Coll[Boolean](tuple37._1 == coll11, tuple37._2 == l5 - placeholder[Long](112) * l5 / placeholder[Long](113) + l33 + l35)))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](114)) {(\n val box32 = OUTPUTS(placeholder[Int](115))\n val tuple33 = box32.tokens(placeholder[Int](116))\n val box34 = OUTPUTS(placeholder[Int](117))\n val tuple35 = box34.tokens(placeholder[Int](118))\n sigmaProp(allOf(Coll[Boolean](bool25, func4((prop3, INPUTS(placeholder[Int](119)))), allOf(Coll[Boolean](func4((prop14, box32)), allOf(Coll[Boolean](tuple33._1 == coll11, tuple33._2 == l5)))), allOf(Coll[Boolean](func4((prop16, box34)), allOf(Coll[Boolean](tuple35._1 == coll11, tuple35._2 == l17)))), func19(coll9))))\n )} else { sigmaProp(placeholder[Boolean](120)) } } } } } } } } }\n}",
"address": "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",
"assets": [
{
"tokenId": "ee727b75fb542f8e09ca486801985e29616d5b5271f240586af95d505e18c7e9",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
"index": 1,
"amount": 20,
"name": "SigUSD",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "5ccd02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508cd02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508",
"sigmaType": "(SSigmaProp, SSigmaProp)",
"renderedValue": "[02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508,02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508]"
},
"R6": {
"serializedValue": "3c0e0e0000",
"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[,]"
},
"R8": {
"serializedValue": "0528",
"sigmaType": "SLong",
"renderedValue": "20"
},
"R7": {
"serializedValue": "550000",
"sigmaType": "(SBoolean, SBoolean)",
"renderedValue": "[false,false]"
},
"R9": {
"serializedValue": "0500",
"sigmaType": "SLong",
"renderedValue": "0"
},
"R4": {
"serializedValue": "049ac8be01",
"sigmaType": "SInt",
"renderedValue": "1561101"
}
}
},
{
"boxId": "f8389119684fa13620c1bf8e31b53880ae83902123dc2ee497522a9aeabff29c",
"value": 1000000,
"index": 1,
"spendingProof": "2d816f09ca3af3756a48aa82ebca5d0d6a232b64ba8923a23297b235a40af8be4ce9b2769c67d37656aa586fa36bf43b19ef2cde4c88b0ad",
"outputBlockId": "d2b38b01add204747fbd78241279a335ba9722bfb5e4b6d7d80b43ee37315bb6",
"outputTransactionId": "7a599abe4ef01af9e3b807297b4ef52c1a4c91d20de0cf7d76bef7e6fda95bfa",
"outputIndex": 0,
"outputGlobalIndex": 48681332,
"outputCreatedAt": 1559997,
"outputSettledAt": 1559998,
"ergoTree": "0008cd02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bd3271,95dfc5,...)))}",
"address": "9fxPJLBUSJ6s5BrStXDrH7coergyyrzdPjmDPDtf8X5inT8DQxs",
"assets": [
{
"tokenId": "f151f5c1aab0d47a82083d210346fb0cf919335a31308e1448ac0bff33eb2209",
"index": 0,
"amount": 1,
"name": "Psychologist Pass",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "50048fe7a1feb6363248be39618c6e100c8ed138710c7bb1fdc74e0cd60695e4",
"value": 925700000,
"index": 2,
"spendingProof": "76c6566fed698aca86a37e130423d7d760d94bea66c08d8f61560c19f671f061a8cc60279fef530cd3df440df92ecdf7d84631ca2b5f5566",
"outputBlockId": "9bac6ae3d581f7928a0ea63c87519de60fa07c08dde0d7aa007ae4cde5d23a2f",
"outputTransactionId": "b2db773e99ba83dd94ad49d83d480feea4d7aa78242ee2dffb0df27742765122",
"outputIndex": 2,
"outputGlobalIndex": 48700445,
"outputCreatedAt": 1560668,
"outputSettledAt": 1560669,
"ergoTree": "0008cd02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bd3271,95dfc5,...)))}",
"address": "9fxPJLBUSJ6s5BrStXDrH7coergyyrzdPjmDPDtf8X5inT8DQxs",
"assets": [
{
"tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
"index": 0,
"amount": 390,
"name": "SigUSD",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "eb0e519402dfd47951b9c6beb7ddc8c9e970802f46f0e8b2a0298c08d7c12e31",
"index": 1,
"amount": 1,
"name": "PsychologistPass",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "c09965e6645f76bfa208304ece7a437ed2daab7cbab57dc228578181f4278c90",
"transactionId": "2ff2810ecd7292a53ae5fb5cff33d5677cc7ea846cdde7d64ebcdc7e352ebaee",
"blockId": "10902cd0ceb38bf4f88ea90deb0370698accfb56f76337886f81b08c6368d625",
"value": 1000000,
"index": 0,
"globalIndex": 48700470,
"creationHeight": 1560669,
"settlementHeight": 1560670,
"ergoTree": "0008cd02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bd3271,95dfc5,...)))}",
"address": "9fxPJLBUSJ6s5BrStXDrH7coergyyrzdPjmDPDtf8X5inT8DQxs",
"assets": [
{
"tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
"index": 0,
"amount": 20,
"name": "SigUSD",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "14a29e6e569c915f1d0f2b0cb5e81b71aba9d8585208bd236605ea298e1ff498",
"mainChain": true
},
{
"boxId": "e393ec12bcac54fb6cbc90d0a777d0ab0060126bfb9f70477471a47ff519f559",
"transactionId": "2ff2810ecd7292a53ae5fb5cff33d5677cc7ea846cdde7d64ebcdc7e352ebaee",
"blockId": "10902cd0ceb38bf4f88ea90deb0370698accfb56f76337886f81b08c6368d625",
"value": 1100000,
"index": 1,
"globalIndex": 48700471,
"creationHeight": 1560669,
"settlementHeight": 1560670,
"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": "783d76875bb4b93152d1ce90947ba1cdf8bf31e0f91279bd6c086ccc5d25d6cb",
"mainChain": true
},
{
"boxId": "44a3eca1f498610a31599851c8006274049d3f18189387d749388f2c4c313764",
"transactionId": "2ff2810ecd7292a53ae5fb5cff33d5677cc7ea846cdde7d64ebcdc7e352ebaee",
"blockId": "10902cd0ceb38bf4f88ea90deb0370698accfb56f76337886f81b08c6368d625",
"value": 925600000,
"index": 2,
"globalIndex": 48700472,
"creationHeight": 1560669,
"settlementHeight": 1560670,
"ergoTree": "0008cd02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bd3271,95dfc5,...)))}",
"address": "9fxPJLBUSJ6s5BrStXDrH7coergyyrzdPjmDPDtf8X5inT8DQxs",
"assets": [
{
"tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
"index": 0,
"amount": 390,
"name": "SigUSD",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "f151f5c1aab0d47a82083d210346fb0cf919335a31308e1448ac0bff33eb2209",
"index": 1,
"amount": 1,
"name": "Psychologist Pass",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "eb0e519402dfd47951b9c6beb7ddc8c9e970802f46f0e8b2a0298c08d7c12e31",
"index": 2,
"amount": 1,
"name": "PsychologistPass",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "14a29e6e569c915f1d0f2b0cb5e81b71aba9d8585208bd236605ea298e1ff498",
"mainChain": true
}
],
"size": 529,
"isUnconfirmed": false
}