Transaction
ID: dda6ec2998...5af0
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0071 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0031 ERG
Tokens:
Outputs (4)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0021 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.006 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
5
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 598,896
Total coins transferred: 0.0102 ERG
Fees: 0.0011 ERG
Fees per byte: 0.0000003 ERG
Raw Transaction Data
{
"id": "dda6ec29983fc093bda93c2574c72497fdb3b3c09fbbbd07845e8730dcc85af0",
"blockId": "74b35e6e87a84b2cf2f13f05c65dcb5910a0655369c2c2aaaa230d16465f70f8",
"inclusionHeight": 1162039,
"timestamp": 1703318600273,
"index": 64,
"globalIndex": 6310385,
"numConfirmations": 598896,
"inputs": [
{
"boxId": "44d1758e0d445e7e6e76af3dd8a4a6ee1ca744d6ab10e16d57d04408e336dd04",
"value": 7100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "f32f74b095dbe5ed29aedb06122c35fca6111c881e0a945f4fe380ec1e609961",
"outputTransactionId": "618875dc63ae2e60d847e149b6aae920c83345406e5fb7e58c96a4e82c12e856",
"outputIndex": 0,
"outputGlobalIndex": 35290742,
"outputCreatedAt": 1162032,
"outputSettledAt": 1162034,
"ergoTree": "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",
"ergoTreeConstants": "",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val tuple2 = (Coll[Byte](), 0L)\n val tuple3 = coll1.getOrElse(0, 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 bool9 = !bool6\n val coll10 = box7.id\n val l11 = OUTPUTS.map(\n {(box11: Box) =>\n box11.tokens.map({(tuple13: (Coll[Byte], Long)) => if (tuple13._1 == coll10) { tuple13._2 } else { 0L } }).fold(\n 0L, {(tuple13: (Long, Long)) => tuple13._1 + tuple13._2 }\n )\n }\n ).fold(0L, {(tuple11: (Long, Long)) => tuple11._1 + tuple11._2 })\n val coll12 = coll8(1)\n val coll13 = coll8(2)\n val coll14 = coll8(3)\n val coll15 = coll8(4)\n val box16 = OUTPUTS(0)\n val coll17 = box16.propositionBytes\n val coll18 = box7.R8[Coll[Long]].get\n val l19 = coll18(6)\n val l20 = l19 + 1000000L\n val coll21 = box7.R5[Coll[Byte]].get\n val bool22 = if (coll17 == SELF.propositionBytes) {\n (\n (((box16.value >= l20) && (box16.R4[Coll[Byte]].get == box7.R4[Coll[Byte]].get)) && (box16.R5[Coll[Byte]].get == coll21)) && (\n box16.R6[Coll[Byte]].get == box7.R6[Coll[Byte]].get\n )\n ) && (box16.R7[Box].get == box7)\n } else { false }\n val l23 = coll18(3)\n val l24 = CONTEXT.preHeader.timestamp\n val l25 = SELF.value\n val l26 = coll18(5)\n val coll27 = box16.tokens\n val tuple28 = coll27.getOrElse(0, tuple2)\n val l29 = tuple3._2\n val l30 = coll18(2)\n val l31 = coll18(4)\n val bool32 = coll18(0) == 0L\n val l33 = tuple28._2\n val tuple34 = coll27.getOrElse(1, tuple2)\n val box35 = OUTPUTS(1)\n val coll36 = Coll[Byte](-27,64,-52,-17,-3,59,-115,-48,-12,1,25,53,118,-52,65,52,103,3,-106,-107,-106,-108,39,-33,-108,69,65,-109,-35,-33,-77,117)\n val bool37 = l24 > l23\n val bool38 = bool6 && (l29 == 1L)\n val bool39 = if (coll18(1) == 0L) { (bool38 && bool37) && (l24 < l23 + 86400000L) } else { bool38 && (l24 <= l23) }\n val tuple40 = coll1.getOrElse(1, tuple2)\n val l41 = tuple40._2\n val l42 = tuple34._2\n val coll43 = tuple34._1\n val coll44 = box35.tokens\n val tuple45 = coll44.getOrElse(0, tuple2)\n val coll46 = tuple45._1\n val l47 = tuple45._2\n val coll48 = if (bool6) { SELF.R8[Coll[Long]].get } else { Coll[Long](0L, 0L) }\n val l49 = coll48(0)\n val l50 = coll48(1)\n val coll51 = tuple28._1\n proveDlog(decodePoint(coll8(0))) && sigmaProp(bool9 && (l11 == 0L)) || sigmaProp(((if ((bool9 && (INPUTS.size == 2)) && (OUTPUTS.size == 3)) {(\n val box52 = INPUTS(1)\n val l53 = box52.value\n val l54 = l25 - l19 - l26 + l53\n val l55 = if (bool32) { l29 / l30 } else { l54 - 2L * l20 / l31 * l30 }\n ((((((((((((((((l53 >= 2000000L) && (blake2b256(box52.R9[Coll[Coll[Byte]]].get(1)) == coll12)) && (blake2b256(box52.R9[Coll[Coll[Byte]]].get(2)) == coll13)) && (blake2b256(box52.R9[Coll[Coll[Byte]]].get(3)) == coll14)) && (blake2b256(box52.R9[Coll[Coll[Byte]]].get(4)) == coll15)) && bool22) && (l23 - l24 < 94608000000L)) && (box16.value == l54)) && (box16.value >= 2L * l20)) && \n val coll56 = coll51\n coll56 == SELF.id\n ) && (l33 == l55 + 1L)) && ((((bool32 && \n val coll56 = coll43\n coll56 == coll21\n ) && (tuple34 == tuple3)) && (coll27.size == 2)) || ((!bool32) && (coll27.size == 1)))) && (box16.R8[Coll[Long]].get(0) == l55)) && (box16.R8[Coll[Long]].get(1) == 0L)) && (blake2b256(box35.propositionBytes) == coll12)) && (box35.value == l26)) && (blake2b256(OUTPUTS(2).propositionBytes) == coll36)\n )} else { false } || if ((bool39 && (INPUTS.size == 2)) && (OUTPUTS.size == 4)) {(\n val l52 = if (bool32) { l41 - l42 } else { l25 - box16.value }\n val l53 = if (bool32) { l52 / l30 } else { l52 / l31 * l30 }\n val tuple54 = INPUTS(1).tokens.getOrElse(0, tuple2)\n val l55 = if (tuple54._1 == coll10) { tuple54._2 } else { 0L }\n (((((((l53 == l55) && bool22) && (((((((((bool32 && (tuple3 == tuple28)) && (box16.value == l25)) && ((coll43 == coll21) || (l42 == 0L))) && (coll46 == coll21)) && (l47 == l52)) && (coll44.size == 1)) && (OUTPUTS(2).value >= l53 * l31 * l30)) && (OUTPUTS(2).tokens.size == 0)) || ((((((!bool32) && (box35.value >= l52)) && (coll44.size == 0)) && (OUTPUTS(2).tokens.getOrElse(0, tuple2)._1 == coll21)) && (OUTPUTS(2).tokens.getOrElse(0, tuple2)._2 >= l53 * l30)) && (OUTPUTS(2).tokens.size == 1)))) && (box16.R8[Coll[Long]].get(0) == l49)) && (box16.R8[Coll[Long]].get(1) == l50 + l55)) && (blake2b256(OUTPUTS(2).propositionBytes) == coll14)) && (blake2b256(OUTPUTS(3).propositionBytes) == coll36)) && (OUTPUTS(3).value <= l19)\n )} else { false }) || if ((bool6 && (INPUTS.size == 1)) && (OUTPUTS.size == 3)) { ((((((((((((box16.value == l25 - l19 - 1000000L) && bool22) && (coll51 == coll4)) && (l33 == 1L)) && (tuple34 == tuple40)) && (box16.R8[Coll[Long]].get(0) == l49)) && (box16.R8[Coll[Long]].get(1) == 0L)) && (blake2b256(box35.propositionBytes) == coll13)) && (box35.value == 1000000L)) && (coll44.size == 1)) && \n val coll52 = coll46\n coll52 == coll4\n ) && (l47 == l29 - 1L)) && (blake2b256(OUTPUTS(2).propositionBytes) == coll36) } else { false }) || if ((bool37 && (!bool39)) || if (bool6) { l50 == l49 } else { false }) { (((((((INPUTS.size == 1) && (OUTPUTS.size == 2)) && (blake2b256(coll17) == coll15)) && (box16.value >= l25 - l19)) && (coll51 == tuple40._1)) && (l33 == l41)) && (l11 == 0L)) && (blake2b256(box35.propositionBytes) == coll36) } else { false })\n}",
"address": "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",
"assets": [
{
"tokenId": "94f359ec9927432faaa220ee663f4cfba263fe7ceae553e25d3e8f584886a70d",
"index": 0,
"amount": 1,
"name": "Put_A_NETA_ERG_1000000_2024-01-22_per_1",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e20472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"sigmaType": "Coll[SByte]",
"renderedValue": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8"
},
"R6": {
"serializedValue": "0e0136",
"sigmaType": "Coll[SByte]",
"renderedValue": "36"
},
"R8": {
"serializedValue": "110280dac40980ade204",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000,5000000]"
},
"R7": {
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"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0e275075745f415f4e4554415f4552475f313030303030305f323032342d30312d32325f7065725f31",
"sigmaType": "Coll[SByte]",
"renderedValue": "5075745f415f4e4554415f4552475f313030303030305f323032342d30312d32325f7065725f31"
}
}
},
{
"boxId": "1b4cbce1f57738949ef21694af0a6e4323b808858b4d15c0a0caf92ed1a781ff",
"value": 3100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "74b35e6e87a84b2cf2f13f05c65dcb5910a0655369c2c2aaaa230d16465f70f8",
"outputTransactionId": "4c41f9af0643548eb478bd83ece90de2d98a6696301cd476faee7dacb89f1e0b",
"outputIndex": 0,
"outputGlobalIndex": 35290846,
"outputCreatedAt": 1162037,
"outputSettledAt": 1162039,
"ergoTree": "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",
"ergoTreeConstants": "",
"ergoTreeScript": "{\n val coll1 = Coll[Byte](-108,17,42,16,110,-95,-128,-91,-47,32,16,-55,-100,-125,-113,-116,4,89,-28,-63,-32,118,-110,-22,-97,-91,45,82,-70,-2,-80,39)\n val tuple2 = (Coll[Byte](), 0L)\n val tuple3 = SELF.tokens.getOrElse(0, tuple2)\n val box4 = OUTPUTS(1)\n val tuple5 = box4.tokens.getOrElse(0, tuple2)\n val l6 = tuple3._2\n SELF.R4[SigmaProp].get && sigmaProp(blake2b256(OUTPUTS(0).propositionBytes) != coll1) || sigmaProp(if ((OUTPUTS.size == 4) && \n val l7 = l6\n l7 > 0L\n ) {(\n val box7 = SELF.R5[Box].get\n val bool8 = tuple3._1 == box7.id\n val l9 = tuple5._2\n val coll10 = box7.R8[Coll[Long]].get\n val l11 = coll10(0)\n val l12 = if (bool8) { l6 } else { 0L }\n val l13 = coll10(2)\n val l14 = coll10(4)\n ((bool8 && (blake2b256(box7.propositionBytes) == coll1)) && (box4.propositionBytes == SELF.R6[Coll[Byte]].get)) && (if ((l9 > 0L) && (l11 == 0L)) {(\n val l15 = l12 * l13\n ((box4.value >= SELF.value - coll10(6) - 1000000L - l15 * l14) && (tuple5._1 == box7.R5[Coll[Byte]].get)) && (l9 == l15)\n )} else { false } || if ((l9 == 0L) && (l11 == 1L)) { box4.value >= l12 * l13 * l14 } else { false })\n )} else { false })\n}",
"address": "DeTTSE3zMiyVGXCLf8SRzGkfccmkzgmp38KcTNq6ESgc8uHNYp6rUhmTiV3sQPpGo2KV5AcQ8TALDBk32NE1qBA4QTonzu5Q5mT2rwWNWKVXi6fCEGhv54pgLZrKnooUXwCmeCmd2L1c6abkLthhkK9WYNQAoXfVT1Fx2kWemgP8GokyJMjLgo7zY1Kbs7JnmsunwXRq59DV8RA96rDq5UkFW9U6Ja3A1SYJ3idYfhLfADbqE7bw8QuXDLKNRJGk2ngfg6KSb98PN5TagNufoeJKPcyJZ4vzwpmtrQPLZwb694S7daz449Xqfko5MSJQNz8ewoD5tx72VFB1KbpmT9CNGe5tyV94z8XZ416soDNboZUGfDCfaV1ijxkjkyf4Bs4KMHdjxwz7G7fZtfUT3ymxqNXpEJy14SzT2U8Z",
"assets": [
{
"tokenId": "94f359ec9927432faaa220ee663f4cfba263fe7ceae553e25d3e8f584886a70d",
"index": 0,
"amount": 5000000,
"name": "Put_A_NETA_ERG_1000000_2024-01-22_per_1",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 1,
"amount": 5000000,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "SSigmaProp",
"renderedValue": "023e90ab7c56ed970ae81ef09ad0a71278dc8b5e0e4eebce2714821d3c26efd508"
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"R5": {
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"sigmaType": null,
"renderedValue": null
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023e90ab7c56ed970ae81ef09ad0a71278dc8b5e0e4eebce2714821d3c26efd508"
}
}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "389a0efea6d988c9fe738767d6e1d42a9f1bdb63e9d7582c4f2d4efbcf00147e",
"transactionId": "dda6ec29983fc093bda93c2574c72497fdb3b3c09fbbbd07845e8730dcc85af0",
"blockId": "74b35e6e87a84b2cf2f13f05c65dcb5910a0655369c2c2aaaa230d16465f70f8",
"value": 2100000,
"index": 0,
"globalIndex": 35290942,
"creationHeight": 1162037,
"settlementHeight": 1162039,
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"ergoTreeConstants": "",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val tuple2 = (Coll[Byte](), 0L)\n val tuple3 = coll1.getOrElse(0, 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 bool9 = !bool6\n val coll10 = box7.id\n val l11 = OUTPUTS.map(\n {(box11: Box) =>\n box11.tokens.map({(tuple13: (Coll[Byte], Long)) => if (tuple13._1 == coll10) { tuple13._2 } else { 0L } }).fold(\n 0L, {(tuple13: (Long, Long)) => tuple13._1 + tuple13._2 }\n )\n }\n ).fold(0L, {(tuple11: (Long, Long)) => tuple11._1 + tuple11._2 })\n val coll12 = coll8(1)\n val coll13 = coll8(2)\n val coll14 = coll8(3)\n val coll15 = coll8(4)\n val box16 = OUTPUTS(0)\n val coll17 = box16.propositionBytes\n val coll18 = box7.R8[Coll[Long]].get\n val l19 = coll18(6)\n val l20 = l19 + 1000000L\n val coll21 = box7.R5[Coll[Byte]].get\n val bool22 = if (coll17 == SELF.propositionBytes) {\n (\n (((box16.value >= l20) && (box16.R4[Coll[Byte]].get == box7.R4[Coll[Byte]].get)) && (box16.R5[Coll[Byte]].get == coll21)) && (\n box16.R6[Coll[Byte]].get == box7.R6[Coll[Byte]].get\n )\n ) && (box16.R7[Box].get == box7)\n } else { false }\n val l23 = coll18(3)\n val l24 = CONTEXT.preHeader.timestamp\n val l25 = SELF.value\n val l26 = coll18(5)\n val coll27 = box16.tokens\n val tuple28 = coll27.getOrElse(0, tuple2)\n val l29 = tuple3._2\n val l30 = coll18(2)\n val l31 = coll18(4)\n val bool32 = coll18(0) == 0L\n val l33 = tuple28._2\n val tuple34 = coll27.getOrElse(1, tuple2)\n val box35 = OUTPUTS(1)\n val coll36 = Coll[Byte](-27,64,-52,-17,-3,59,-115,-48,-12,1,25,53,118,-52,65,52,103,3,-106,-107,-106,-108,39,-33,-108,69,65,-109,-35,-33,-77,117)\n val bool37 = l24 > l23\n val bool38 = bool6 && (l29 == 1L)\n val bool39 = if (coll18(1) == 0L) { (bool38 && bool37) && (l24 < l23 + 86400000L) } else { bool38 && (l24 <= l23) }\n val tuple40 = coll1.getOrElse(1, tuple2)\n val l41 = tuple40._2\n val l42 = tuple34._2\n val coll43 = tuple34._1\n val coll44 = box35.tokens\n val tuple45 = coll44.getOrElse(0, tuple2)\n val coll46 = tuple45._1\n val l47 = tuple45._2\n val coll48 = if (bool6) { SELF.R8[Coll[Long]].get } else { Coll[Long](0L, 0L) }\n val l49 = coll48(0)\n val l50 = coll48(1)\n val coll51 = tuple28._1\n proveDlog(decodePoint(coll8(0))) && sigmaProp(bool9 && (l11 == 0L)) || sigmaProp(((if ((bool9 && (INPUTS.size == 2)) && (OUTPUTS.size == 3)) {(\n val box52 = INPUTS(1)\n val l53 = box52.value\n val l54 = l25 - l19 - l26 + l53\n val l55 = if (bool32) { l29 / l30 } else { l54 - 2L * l20 / l31 * l30 }\n ((((((((((((((((l53 >= 2000000L) && (blake2b256(box52.R9[Coll[Coll[Byte]]].get(1)) == coll12)) && (blake2b256(box52.R9[Coll[Coll[Byte]]].get(2)) == coll13)) && (blake2b256(box52.R9[Coll[Coll[Byte]]].get(3)) == coll14)) && (blake2b256(box52.R9[Coll[Coll[Byte]]].get(4)) == coll15)) && bool22) && (l23 - l24 < 94608000000L)) && (box16.value == l54)) && (box16.value >= 2L * l20)) && \n val coll56 = coll51\n coll56 == SELF.id\n ) && (l33 == l55 + 1L)) && ((((bool32 && \n val coll56 = coll43\n coll56 == coll21\n ) && (tuple34 == tuple3)) && (coll27.size == 2)) || ((!bool32) && (coll27.size == 1)))) && (box16.R8[Coll[Long]].get(0) == l55)) && (box16.R8[Coll[Long]].get(1) == 0L)) && (blake2b256(box35.propositionBytes) == coll12)) && (box35.value == l26)) && (blake2b256(OUTPUTS(2).propositionBytes) == coll36)\n )} else { false } || if ((bool39 && (INPUTS.size == 2)) && (OUTPUTS.size == 4)) {(\n val l52 = if (bool32) { l41 - l42 } else { l25 - box16.value }\n val l53 = if (bool32) { l52 / l30 } else { l52 / l31 * l30 }\n val tuple54 = INPUTS(1).tokens.getOrElse(0, tuple2)\n val l55 = if (tuple54._1 == coll10) { tuple54._2 } else { 0L }\n (((((((l53 == l55) && bool22) && (((((((((bool32 && (tuple3 == tuple28)) && (box16.value == l25)) && ((coll43 == coll21) || (l42 == 0L))) && (coll46 == coll21)) && (l47 == l52)) && (coll44.size == 1)) && (OUTPUTS(2).value >= l53 * l31 * l30)) && (OUTPUTS(2).tokens.size == 0)) || ((((((!bool32) && (box35.value >= l52)) && (coll44.size == 0)) && (OUTPUTS(2).tokens.getOrElse(0, tuple2)._1 == coll21)) && (OUTPUTS(2).tokens.getOrElse(0, tuple2)._2 >= l53 * l30)) && (OUTPUTS(2).tokens.size == 1)))) && (box16.R8[Coll[Long]].get(0) == l49)) && (box16.R8[Coll[Long]].get(1) == l50 + l55)) && (blake2b256(OUTPUTS(2).propositionBytes) == coll14)) && (blake2b256(OUTPUTS(3).propositionBytes) == coll36)) && (OUTPUTS(3).value <= l19)\n )} else { false }) || if ((bool6 && (INPUTS.size == 1)) && (OUTPUTS.size == 3)) { ((((((((((((box16.value == l25 - l19 - 1000000L) && bool22) && (coll51 == coll4)) && (l33 == 1L)) && (tuple34 == tuple40)) && (box16.R8[Coll[Long]].get(0) == l49)) && (box16.R8[Coll[Long]].get(1) == 0L)) && (blake2b256(box35.propositionBytes) == coll13)) && (box35.value == 1000000L)) && (coll44.size == 1)) && \n val coll52 = coll46\n coll52 == coll4\n ) && (l47 == l29 - 1L)) && (blake2b256(OUTPUTS(2).propositionBytes) == coll36) } else { false }) || if ((bool37 && (!bool39)) || if (bool6) { l50 == l49 } else { false }) { (((((((INPUTS.size == 1) && (OUTPUTS.size == 2)) && (blake2b256(coll17) == coll15)) && (box16.value >= l25 - l19)) && (coll51 == tuple40._1)) && (l33 == l41)) && (l11 == 0L)) && (blake2b256(box35.propositionBytes) == coll36) } else { false })\n}",
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{
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"name": "Put_A_NETA_ERG_1000000_2024-01-22_per_1",
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}
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"sigmaType": "Coll[SByte]",
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{
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"ergoTree": "0008cd023e90ab7c56ed970ae81ef09ad0a71278dc8b5e0e4eebce2714821d3c26efd508",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3e90ab,93deef,...)))}",
"address": "9ezcf4GFUNVreCRyuPL99ihyumrM4JNsX4Cz9w7f3YBaPQC1pt1",
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3e90ab,93deef,...)))}",
"address": "9ezcf4GFUNVreCRyuPL99ihyumrM4JNsX4Cz9w7f3YBaPQC1pt1",
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{
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"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)}",
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}
],
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}