Transaction
ID: 8974553e48...80e3
Inputs (1)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.5096 ERG
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.5064 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0022 ERG
Transaction Details
Confirmations: 23,593
Total coins transferred: 0.5096 ERG
Fees: 0.0022 ERG
Fees per byte: 0.000000694 ERG
Raw Transaction Data
{
"id": "8974553e48a74df9caee58587021dbb0ae8e4e8fd8c74667f904d9afee9180e3",
"blockId": "554796cae1a891dcfc1ce82bbedcbee7b4a0a9e983a663deb7d89ff9d1f1c224",
"inclusionHeight": 1746152,
"timestamp": 1774024501703,
"index": 2,
"globalIndex": 10474204,
"numConfirmations": 23593,
"inputs": [
{
"boxId": "4bb18ad87273ba7bda42e7f97012a65eb97d82448b753610d5168121bb1a50e7",
"value": 509600000,
"index": 0,
"spendingProof": "c90689d15abc390b528bd53e788a4b0175c76c658504d48c32704090a8a265e1b5707eacd6760c320da515fbf03b9eb550b85e10f9bb3e52",
"outputBlockId": "554796cae1a891dcfc1ce82bbedcbee7b4a0a9e983a663deb7d89ff9d1f1c224",
"outputTransactionId": "464437dad9222769a4963e253d71638841370dc86d3054fb801ab2c91417b4e8",
"outputIndex": 0,
"outputGlobalIndex": 54245030,
"outputCreatedAt": 1746151,
"outputSettledAt": 1746152,
"ergoTree": "0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bda269,1a4560,...)))}",
"address": "9huKeYQbBnuGcndNCSbxUrRc2sRQNCvfyex8nMorKkEwLcQW4vd",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0e0139",
"sigmaType": "Coll[SByte]",
"renderedValue": "39"
},
"R8": {
"serializedValue": "110b0000c09a0ce293d50180ea3080897a80c78c02220000d00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0,100000,1746161,400000,1000000,2200000,17,0,0,1000]"
},
"R7": {
"serializedValue": "63c097f5070008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577be4c96a01a55b8735ed1a99e46c2c89f8994aacdf4b1109bdcf682f1e5b34479c6e39266998750059024470e33a86373ff90d6de842cf5fd3ed2f092e444af8f065c438ee82bb3507",
"sigmaType": null,
"renderedValue": null
},
"R9": {
"serializedValue": "1a022103bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b240008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b,0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b]"
},
"R4": {
"serializedValue": "0e1354455354204552472043616c6c2024302e3430",
"sigmaType": "Coll[SByte]",
"renderedValue": "54455354204552472043616c6c2024302e3430"
}
}
}
],
"dataInputs": [
{
"boxId": "ac99a1eadde51e62cb48b85731e46ef56136a0a2c2c0d035416475f79e736ef0",
"value": 150000000,
"index": 0,
"outputBlockId": "a0572fca9270bb8f8253e852730a68dadb254a03b7e96cfd573736e51e63a85e",
"outputTransactionId": "16ac127b686954c7163ac83517e271083b90f1e79438d8a2fe08236efef46552",
"outputIndex": 0,
"ergoTree": "10040e20ea7b36e294b1a954a80752eac288711728e5b91b0b3c0596548c755665050b88040004000400d804d6017300d602b2a5730100d603b1e4c67202041ad604b1e4c672020511ea02d1ededededededed938cb2db6308a7730200017201938cb2db6308720273030001720193c27202c2a7927203b1e4c6a7041a927204b1e4c6a70511937203720492c17202c1a7e6c672020608e4c6a70608",
"address": "QqJr1n1xDwmVKHreupY52BAX35qjNng6DCjpvB2dUpqTWaBxXtHJvuY5qFYg25xQ8fQ7kFdodBmXqGDAoRcsJHoaTt4MvjCyAz2hJPpG1Br9o3YBwoFvJyufMSjTwbSVGrPKSxPq9f1TBpJuthgw7rMgd6DDwDndMyiQ4M9wnm9FXuup12EzDTZavsJ1D6bPD81eS1iR6ppRNcVyEbAr95kRkry",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1a1520203ef3066a912f35c488487cc2cb94bdb0d30680dab22551c7e6fdbc70dfcc8e207a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b020050322548722d36f094e341f59ed93eb22118b363eb4efe8c461a52c4d93e2c32048132396ebd00831e603c73cf01e01f248dd1966d2cc976caf52ef76f7ac6e3620e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c29700000000000000000000000000206122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad0000",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[203ef3066a912f35c488487cc2cb94bdb0d30680dab22551c7e6fdbc70dfcc8e,7a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b0,050322548722d36f094e341f59ed93eb22118b363eb4efe8c461a52c4d93e2c3,48132396ebd00831e603c73cf01e01f248dd1966d2cc976caf52ef76f7ac6e36,e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297,,,,,,,,,,,,,,6122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad,,]"
},
"R5": {
"serializedValue": "111580a8d6b9078084af5f80a8d6b90780897a80897a00000000000000000000000080a8d6b907fee5030000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1000000000,100000000,1000000000,1000000,1000000,0,0,0,0,0,0,0,0,0,0,0,0,1000000000,31103,0,0]"
},
"R6": {
"serializedValue": "08cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"sigmaType": "SSigmaProp",
"renderedValue": "03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b"
}
}
}
],
"outputs": [
{
"boxId": "a431d2977fd38b6fc10db6e65a5157d66cba620b9948d8f18fbb32374bd9852f",
"transactionId": "8974553e48a74df9caee58587021dbb0ae8e4e8fd8c74667f904d9afee9180e3",
"blockId": "554796cae1a891dcfc1ce82bbedcbee7b4a0a9e983a663deb7d89ff9d1f1c224",
"value": 506400000,
"index": 0,
"globalIndex": 54245033,
"creationHeight": 1746151,
"settlementHeight": 1746152,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 8\n5: 7\n6: Coll(-22,123,54,-30,-108,-79,-87,84,-88,7,82,-22,-62,-120,113,23,40,-27,-71,27,11,60,5,-106,84,-116,117,86,101,5,11,-120)\n7: Coll(-91,91,-121,53,-19,26,-103,-28,108,44,-119,-8,-103,74,-84,-33,75,17,9,-67,-49,104,47,30,91,52,71,-100,110,57,38,105)\n8: Coll(3,-6,-14,-53,50,-97,46,-112,-42,-46,59,88,-39,27,-69,108,4,106,-95,67,38,28,-62,31,82,-5,-30,-126,75,-4,-65,4)\n9: 10\n10: 4\n11: 6\n12: 1000000\n13: false\n14: 5\n15: 0\n16: 0\n17: 1\n18: 2\n19: 9\n20: 1\n21: 1\n22: 1\n23: 0\n24: 3\n25: 5\n26: 1\n27: 0\n28: 0\n29: 0\n30: 0\n31: 1\n32: 2\n33: 1\n34: 3\n35: 0\n36: 1000000\n37: 0\n38: 0\n39: 0\n40: 17\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 1000\n47: 100\n48: 1000\n49: 0\n50: 100\n51: 0\n52: 2\n53: 0\n54: 17\n55: 1\n56: 2\n57: 17\n58: 0\n59: 17\n60: 1000000\n61: 0\n62: 3\n63: 2000000\n64: 1\n65: 1\n66: 1\n67: 1\n68: 2\n69: 1\n70: 1000000\n71: 0\n72: 1\n73: 2\n74: 1\n75: 0\n76: false\n77: 1\n78: 3\n79: 1000000\n80: 1\n81: 1000000\n82: 1\n83: 1\n84: false\n85: 0\n86: 0\n87: 0\n88: 0\n89: 0\n90: 1000000\n91: 1000000\n92: 0\n93: 0\n94: 1000\n95: 0\n96: 17\n97: 0\n98: 17\n99: 2\n100: 1\n101: 2\n102: 1\n103: 1\n104: 2\n105: 1\n106: false\n107: 1\n108: 0\n109: 1\n110: 0\n111: 0\n112: 0\n113: 0\n114: 1000000\n115: 1\n116: 0\n117: Coll(-9,-16,8,-83,-113,-54,-83,68,-112,-40,-25,-118,-74,-45,-15,30,-2,114,19,-95,63,123,36,55,-107,-127,-117,21,94,26,-52,-110)\n118: 0\n119: 0\n120: false\n121: 2\n122: false",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val tuple2 = (Coll[Byte](), placeholder[Long](0))\n val tuple3 = coll1.getOrElse(placeholder[Int](1), tuple2)\n val coll4 = tuple3._1\n val box5 = SELF.R7[Box].get\n val bool6 = (coll4 == box5.id) && (SELF.propositionBytes == box5.propositionBytes)\n val box7 = if (bool6) { box5 } else { SELF }\n val coll8 = box7.R9[Coll[Coll[Byte]]].get\n val prop9 = proveDlog(decodePoint(coll8(placeholder[Int](2))))\n val bool10 = !bool6\n val box11 = OUTPUTS(placeholder[Int](3))\n val coll12 = box11.propositionBytes\n val coll13 = prop9.propBytes\n val coll14 = box7.R8[Coll[Long]].get\n val l15 = coll14(placeholder[Int](4))\n val l16 = coll14(placeholder[Int](5))\n val coll17 = placeholder[Coll[Byte]](6)\n val coll18 = placeholder[Coll[Byte]](7)\n val coll19 = placeholder[Coll[Byte]](8)\n val l20 = coll14(placeholder[Int](9))\n val l21 = coll14(placeholder[Int](10))\n val l22 = coll14(placeholder[Int](11))\n val l23 = l22 + placeholder[Long](12)\n val coll24 = box7.R5[Coll[Byte]].get\n val bool25 = if (coll12 == SELF.propositionBytes) {\n (\n (\n (\n (((box11.value >= l23) && (box11.R4[Coll[Byte]].get == box7.R4[Coll[Byte]].get)) && (box11.R5[Coll[Byte]].get == coll24)) && (\n box11.R6[Coll[Byte]].get == box7.R6[Coll[Byte]].get\n )\n ) && (box11.R7[Box].get == box7)\n ) && (box11.R8[Coll[Long]].get == coll14)\n ) && (box11.R9[Coll[Coll[Byte]]].get == coll8)\n } else { placeholder[Boolean](13) }\n val l26 = coll14(placeholder[Int](14))\n val coll27 = box11.tokens\n val tuple28 = coll27.getOrElse(placeholder[Int](15), tuple2)\n val coll29 = tuple28._1\n val l30 = coll14(placeholder[Int](16))\n val tuple31 = coll27.getOrElse(placeholder[Int](17), tuple2)\n val l32 = tuple3._2\n val l33 = coll14(placeholder[Int](18))\n val l34 = tuple28._2\n val coll35 = tuple31._1\n val l36 = coll14(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool6 && (l32 == placeholder[Long](21))\n val tuple40 = coll1.getOrElse(placeholder[Int](22), tuple2)\n val tuple41 = coll38.getOrElse(placeholder[Int](23), tuple2)\n val l42 = HEIGHT.toLong\n val l43 = coll14(placeholder[Int](24))\n val l44 = l43 + placeholder[Long](25)\n val bool45 = if (coll14(placeholder[Int](26)) == placeholder[Long](27)) { (bool39 && (l42 >= l43)) && (l42 <= l44) } else { bool39 && (l42 <= l44) }\n val l46 = INPUTS.fold(placeholder[Long](28), {(tuple46: (Long, Box)) =>\n val box48 = tuple46._2\n val coll49 = box48.tokens\n val l50 = tuple46._1\n if ((coll49.size > placeholder[Int](29)) && (box48.id != SELF.id)) {(\n val tuple51 = coll49(placeholder[Int](30))\n if (tuple51._1 == box7.id) { l50 + tuple51._2 } else { l50 }\n )} else { l50 }\n })\n val bool47 = (bool25 && \n val coll47 = coll29\n coll47 == coll4\n ) && (l34 == placeholder[Long](31))\n prop9 && sigmaProp((bool10 && (OUTPUTS.size == placeholder[Int](32))) && (coll12 == coll13)) || sigmaProp(\n (((if ((bool10 && (INPUTS.size == placeholder[Int](33))) && (OUTPUTS.size == placeholder[Int](34))) {(\n val bool48 = l15 == placeholder[Long](35)\n val l49 = l21 * l20 / placeholder[Long](36)\n val bool50 = l49 > placeholder[Long](37)\n (((((((((if (bool48) {(\n val box51 = CONTEXT.dataInputs(placeholder[Int](38))\n val i52 = l16.toInt\n val l53 = box51.R5[Coll[Long]].get(i52)\n val bool54 = box51.tokens(placeholder[Int](39))._1 == coll17\n val coll55 = box51.R4[Coll[Coll[Byte]]].get(i52)\n if (l16 == placeholder[Long](40)) { bool54 && (l53 > placeholder[Long](41)) } else { ((bool54 && (coll55.size > placeholder[Int](42))) && (l53 > placeholder[Long](43))) && (coll1(placeholder[Int](44))._1 == coll55) }\n )} else {(\n val coll51 = coll1(placeholder[Int](45))._1\n (coll51 == coll18) || (coll51 == coll19)\n )} && if (bool48) { (l20 == placeholder[Long](46)) || (l20 == placeholder[Long](47)) } else { ((l20 == placeholder[Long](48)) && (coll1(placeholder[Int](49))._1 == coll18)) || ((l20 == placeholder[Long](50)) && (coll1(placeholder[Int](51))._1 == coll19)) }) && bool50) && bool25) && (box11.value == SELF.value - l22 - l26)) && (box11.value >= placeholder[Long](52) * l23)) && (coll29 == SELF.id)) && \n val bool51 = l30 == placeholder[Long](53)\n ((((((((bool51 && bool48) && (l16 != placeholder[Long](54))) && \n val coll52 = coll35\n coll52 == coll24\n ) && (tuple31 == tuple3)) && (l34 == l32 / l33 + placeholder[Long](55))) && (coll27.size == placeholder[Int](56))) || (((bool51 && bool48) && (l16 == placeholder[Long](57))) && \n val l52 = l33 * CONTEXT.dataInputs(placeholder[Int](58)).R5[Coll[Long]].get(placeholder[Int](59)) / placeholder[Long](60)\n val l53 = SELF.value\n (((l52 > placeholder[Long](61)) && (l34 == l53 - placeholder[Long](62) * l22 - l26 - placeholder[Long](63) / l52 + placeholder[Long](64))) && (coll27.size == placeholder[Int](65))) && (box11.value >= l53 - l22 - l26)\n )) || (((((((l30 == placeholder[Long](66)) && bool48) && (coll35 == coll24)) && (tuple31 == tuple3)) && bool50) && (l34 == l32 / l49 + placeholder[Long](67))) && (coll27.size == placeholder[Int](68)))) || ((l15 == placeholder[Long](69)) && \n val l52 = l36 * l20 / placeholder[Long](70)\n ((((l52 > placeholder[Long](71)) && (coll35 == coll24)) && (tuple31 == tuple3)) && (l34 == l32 / l52 + placeholder[Long](72))) && (coll27.size == placeholder[Int](73))\n )\n ) && (box37.propositionBytes == coll8(placeholder[Int](74)))) && (coll38.size == placeholder[Int](75))) && (box37.value >= l26)\n )} else { placeholder[Boolean](76) } || if (((bool6 && (!bool39)) && (INPUTS.size == placeholder[Int](77))) && (OUTPUTS.size == placeholder[Int](78))) { (((((((((box11.value == SELF.value - l22 - placeholder[Long](79)) && bool25) && (coll29 == coll4)) && (l34 == placeholder[Long](80))) && (tuple31 == tuple40)) && (box37.propositionBytes == coll13)) && (box37.value == placeholder[Long](81))) && (coll38.size == placeholder[Int](82))) && (tuple41._1 == coll4)) && (tuple41._2 == l32 - placeholder[Long](83)) } else { placeholder[Boolean](84) }) || if ((bool45 && (l15 == placeholder[Long](85))) && (l46 > placeholder[Long](86))) {(\n val box48 = CONTEXT.dataInputs(placeholder[Int](87))\n val i49 = l16.toInt\n val l50 = box48.R5[Coll[Long]].get(i49)\n val bool51 = l50 > placeholder[Long](88)\n val bool52 = box48.tokens(placeholder[Int](89))._1 == coll17\n val l53 = l33 * l50 / placeholder[Long](90)\n val l54 = l21 * l20 / placeholder[Long](91)\n val bool55 = (l53 > placeholder[Long](92)) && (l54 > placeholder[Long](93))\n val l56 = l53 * l46\n val coll57 = if (l20 == placeholder[Long](94)) { coll18 } else { coll19 }\n val l58 = l54 * l46\n val coll59 = box48.R4[Coll[Coll[Byte]]].get(i49)\n val bool60 = (coll59.size > placeholder[Int](95)) || (l16 == placeholder[Long](96))\n if (l30 == placeholder[Long](97)) { if (l16 == placeholder[Long](98)) {(\n val box61 = OUTPUTS(placeholder[Int](99))\n (((((bool52 && bool51) && bool55) && (box37.value >= l56)) && ((box61.propositionBytes == coll13) && box61.tokens.exists({(tuple62: (Coll[Byte], Long)) => (tuple62._1 == coll57) && (tuple62._2 >= l58) }))) && bool47) && (box11.value >= SELF.value - l56 - l22)\n )} else {(\n val tuple61 = coll1(placeholder[Int](100))\n val box62 = OUTPUTS(placeholder[Int](101))\n val tuple63 = coll27(placeholder[Int](102))\n (((((((((bool52 && bool60) && bool51) && bool55) && (tuple61._1 == coll59)) && coll38.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll59) && (tuple64._2 >= l56) })) && ((box62.propositionBytes == coll13) && box62.tokens.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll57) && (tuple64._2 >= l58) }))) && (tuple63._1 == coll59)) && bool47) && (box11.value >= SELF.value - l22)) && (tuple63._2 >= tuple61._2 - l56)\n )} } else {(\n val tuple61 = coll1(placeholder[Int](103))\n val coll62 = tuple61._1\n val box63 = OUTPUTS(placeholder[Int](104))\n val tuple64 = coll27(placeholder[Int](105))\n (((((((((bool52 && bool60) && bool51) && bool55) && ((coll62 == coll18) || (coll62 == coll19))) && coll38.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll62) && (tuple65._2 >= l58) })) && ((box63.propositionBytes == coll13) && box63.tokens.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll59) && (tuple65._2 >= l56) }))) && (tuple64._1 == coll62)) && bool47) && (box11.value >= SELF.value - l22)) && (tuple64._2 >= tuple61._2 - l58)\n )}\n )} else { placeholder[Boolean](106) }) || if ((bool45 && (l15 == placeholder[Long](107))) && (l46 > placeholder[Long](108))) {(\n val tuple48 = coll1(placeholder[Int](109))\n val coll49 = tuple48._1\n val box50 = CONTEXT.dataInputs(placeholder[Int](110))\n val l51 = box50.R4[Coll[Long]].get(l16.toInt)\n val l52 = if (l30 == placeholder[Long](111)) { if (l51 > l21) {(\n val l52 = l51 - l21\n if (l52 > l36) { l36 } else { l52 }\n )} else { placeholder[Long](112) } } else { if (l51 < l21) {(\n val l52 = l21 - l51\n if (l52 > l36) { l36 } else { l52 }\n )} else { placeholder[Long](113) } }\n val l53 = l52 * l20 / placeholder[Long](114)\n val l54 = l53 * l46\n val tuple55 = coll27(placeholder[Int](115))\n (((((((((coll49 == coll18) || (coll49 == coll19)) && (box50.tokens(placeholder[Int](116))._1 == placeholder[Coll[Byte]](117))) && (l52 > placeholder[Long](118))) && (l53 > placeholder[Long](119))) && coll38.exists({(tuple56: (Coll[Byte], Long)) => (tuple56._1 == coll49) && (tuple56._2 >= l54) })) && (tuple55._1 == coll49)) && bool47) && (box11.value >= SELF.value - l22)) && (tuple55._2 >= tuple48._2 - l54)\n )} else { placeholder[Boolean](120) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](121)) && (coll12 == coll13)) && (box11.value >= SELF.value - l22)) && (coll29 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](122) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "4bb18ad87273ba7bda42e7f97012a65eb97d82448b753610d5168121bb1a50e7",
"index": 0,
"amount": 6,
"name": "TEST ERG Call $0.40",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0e0139",
"sigmaType": "Coll[SByte]",
"renderedValue": "39"
},
"R8": {
"serializedValue": "110b0000c09a0ce293d50180ea3080897a80c78c02220000d00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0,100000,1746161,400000,1000000,2200000,17,0,0,1000]"
},
"R7": {
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"sigmaType": null,
"renderedValue": null
},
"R9": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b,0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b]"
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"R4": {
"serializedValue": "0e1354455354204552472043616c6c2024302e3430",
"sigmaType": "Coll[SByte]",
"renderedValue": "54455354204552472043616c6c2024302e3430"
}
},
"spentTransactionId": "19e620f6035d0ec906f73bb08bb7b6ee268dffab1582c97df452b7f647254c47",
"mainChain": true
},
{
"boxId": "34740d1b1c93013e9ec0a86667d8c518ac6e76175b1e89596aa6d5df4278d197",
"transactionId": "8974553e48a74df9caee58587021dbb0ae8e4e8fd8c74667f904d9afee9180e3",
"blockId": "554796cae1a891dcfc1ce82bbedcbee7b4a0a9e983a663deb7d89ff9d1f1c224",
"value": 1000000,
"index": 1,
"globalIndex": 54245034,
"creationHeight": 1746151,
"settlementHeight": 1746152,
"ergoTree": "0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bda269,1a4560,...)))}",
"address": "9huKeYQbBnuGcndNCSbxUrRc2sRQNCvfyex8nMorKkEwLcQW4vd",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "0632475622e556ac89b5abb475afdbee8edcb236be1789798b2673cc49e52ea9",
"mainChain": true
},
{
"boxId": "05e06ff4e49607ed6c54c29284023185018329c673bd4c6977aab8867e5ac795",
"transactionId": "8974553e48a74df9caee58587021dbb0ae8e4e8fd8c74667f904d9afee9180e3",
"blockId": "554796cae1a891dcfc1ce82bbedcbee7b4a0a9e983a663deb7d89ff9d1f1c224",
"value": 2200000,
"index": 2,
"globalIndex": 54245035,
"creationHeight": 1746151,
"settlementHeight": 1746152,
"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": "c23537db903f517208b5f7aa993afdefff6eea6a9bf46a720ffc7808cd5e39bb",
"mainChain": true
}
],
"size": 3168,
"isUnconfirmed": false
}