Transaction
ID: e2b477d3cb...2b99
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
993.3 ERG
Tokens:
Loading assets...
Outputs (7)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.5 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00185 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
992.79 ERG
Tokens:
Loading assets...
Transaction Details
Status: Confirmed
Size: 15.48 KB
Received time: 10/24/2024 01:33:20 PM
Included in blocks: 1,380,543
Confirmations: 383,047
Total coins transferred: 994.3 ERG
Fees: 0.00185 ERG
Fees per byte: 0.000000117 ERG
Raw Transaction Data
{
"id": "e2b477d3cb14bd2a06c6469b67d669964fc213628224bbe36f34a96a47bd2b99",
"blockId": "f132ce71b8f450aa8eeface90c0abdc42e94c54ff657b4ef0beb76237b0126c0",
"inclusionHeight": 1380543,
"timestamp": 1729776800896,
"index": 5,
"globalIndex": 7948239,
"numConfirmations": 383047,
"inputs": [
{
"boxId": "b1e837cdc6f3703d5dd3ba9496b684fca89c511a687dd1c02fa3a30819a19d05",
"value": 1000000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "8fbc1db48ae46e08fe081bce0c8bc3e1981ed9861a83bc89abe10c02d64300d5",
"outputTransactionId": "b2fcb9f7bbb9242fd255ba4931c032b475e2dcc791547d88c2d93dac8e638a3b",
"outputIndex": 0,
"outputGlobalIndex": 43410881,
"outputCreatedAt": 1380433,
"outputSettledAt": 1380435,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
"ergoTreeScript": "{\n val coll1 = placeholder[Coll[Byte]](0)\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val func3 = {(box3: Box) => box3.R4[AvlTree].get }\n val coll4 = Coll[Byte](\n 3.toByte, -99.toByte, 42.toByte, 10.toByte, 33.toByte, -115.toByte, 124.toByte, 72.toByte, -56.toByte, -3.toByte, 70.toByte, -88.toByte, -46.toByte, -108.toByte, 49.toByte, -67.toByte, 5.toByte, 108.toByte, -124.toByte, -120.toByte, 42.toByte, 33.toByte, 106.toByte, 86.toByte, 115.toByte, 38.toByte, -61.toByte, -57.toByte, -104.toByte, 78.toByte, -56.toByte, 53.toByte\n )\n val func5 = {(opt5: Option[Coll[Byte]]) => opt5.get.slice(1, 33) }\n val func6 = {(box6: Box) => box6.tokens(0) }\n val func7 = {(box7: Box) => box7.tokens(1) }\n val func8 = {(box8: Box) => box8.tokens(2) }\n val func9 = {(tuple9: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple11 = tuple9._2\n val l12 = tuple11._1\n val tuple13 = tuple11._2\n val l14 = tuple13._1\n val l15 = tuple13._2\n tuple9._1.map({(coll16: Coll[Byte]) => if (coll16.size == 9) {(\n val l18 = byteArrayToLong(coll16.slice(1, 9))\n if (l18 < l12) { l12 } else { if (l18 > l14) { l14 } else { l18 } }\n )} else { l15 } }).getOrElse(l15)\n }\n val b10 = getVar[Byte](0.toByte).get\n val i11 = INPUTS.indexOf(SELF, 0)\n val func12 = {(l12: Long) =>\n if (l12 < 128L) { 1 } else {\n if (l12 < 16384L) { 2 } else {\n if (l12 < 2097152L) { 3 } else {\n if (l12 < 268435456L) { 4 } else {\n if (l12 < 34359738368L) { 5 } else {\n if (l12 < 4398046511104L) { 6 } else { if (l12 < 562949953421312L) { 7 } else { if (l12 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b13: Byte) => if (b13 == 11.toByte) {(\n val box15 = OUTPUTS(0)\n val coll16 = CONTEXT.dataInputs\n val box17 = getVar[Box](2.toByte).get\n val coll18 = box17.propositionBytes\n val coll19 = getVar[Coll[Box]](3.toByte).get\n val coll20 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll21 = func3(func2((coll16, coll1))(0)).getMany(Coll[Coll[Byte]](coll4, Coll[Byte](-16.toByte, 54.toByte, 125.toByte, -33.toByte, 52.toByte, 53.toByte, -104.toByte, 31.toByte, 74.toByte, -91.toByte, 87.toByte, 27.toByte, -111.toByte, -35.toByte, 70.toByte, -2.toByte, -127.toByte, 54.toByte, 103.toByte, -14.toByte, -120.toByte, -115.toByte, 79.toByte, -58.toByte, -111.toByte, -106.toByte, -113.toByte, -34.toByte, 21.toByte, -121.toByte, -101.toByte, -105.toByte), Coll[Byte](88.toByte, 30.toByte, -80.toByte, 92.toByte, -24.toByte, 20.toByte, -36.toByte, 63.toByte, 36.toByte, 121.toByte, -28.toByte, -80.toByte, 2.toByte, 125.toByte, -79.toByte, -59.toByte, 73.toByte, 79.toByte, -28.toByte, 32.toByte, 61.toByte, 117.toByte, -124.toByte, 18.toByte, 101.toByte, -10.toByte, -57.toByte, 82.toByte, -105.toByte, -43.toByte, -20.toByte, -63.toByte), blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 112.toByte, 114.toByte, 111.toByte, 112.toByte, 111.toByte, 115.toByte, 97.toByte, 108.toByte, 46.toByte).append(coll18))).append(coll19.map({(box21: Box) => blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(box21.propositionBytes)) })), coll20(1))\n val tuple22 = func7(box15)\n val tuple23 = func7(SELF)\n val coll24 = tuple23._1\n val l25 = tuple23._2\n val tuple26 = func8(box15)\n val tuple27 = func8(SELF)\n val coll28 = tuple27._1\n val i29 = coll19.size\n val box30 = OUTPUTS(1)\n val l31 = box30.value\n val l32 = 9223372036854775807L - l25\n val tuple33 = {(box33: Box) => box33.tokens(0) }(box30)\n val tuple34 = {(box34: Box) => box34.tokens(1) }(box30)\n val coll35 = box30.propositionBytes\n val coll36 = OUTPUTS.slice(2, i29 + 2)\n val box37 = func2((coll16, placeholder[Coll[Byte]](3)))(0)\n val coll38 = coll20(2)\n allOf(Coll[Boolean](allOf(Coll[Boolean](blake2b256(box15.propositionBytes) == func5(coll21(0)), box15.value >= SELF.value, func6(box15) == func6(SELF), tuple22._1 == coll24, tuple22._2 == l25 - 1L, tuple26._1 == coll28, tuple26._2 == tuple27._2 - i29.toLong, box15.tokens.size == 3)), allOf(Coll[Boolean](l31 >= box17.value, l31 >= 5000000L, {(box39: Box) => box39.R4[Coll[Int]].get(0) }(box30).toLong == l32, tuple33._1 == coll24, tuple33._2 == 1L, tuple34._1 == placeholder[Coll[Byte]](2), tuple34._2 == func9((func3(func2((coll16, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.toByte)), coll20(0))(0), (0L, (100000000000L, 1000L)))), coll35 == coll18, {(box39: Box) => box39.R5[Coll[Long]].get(0) }(box30) >= CONTEXT.preHeader.timestamp + func9((coll21(1), (43200000L, (2626560000L, 86400000L)))), blake2b256(coll35) == func5(coll21(3)), {(box39: Box) => box39.R5[Coll[Long]].get(1) }(box30) == 0L, {(box39: Box) =>\n val coll41 = box39.R5[Coll[Long]].get\n coll41.slice(2, coll41.size)\n }(box30).forall({(l39: Long) => l39 == 0L }))), coll36.indices.forall({(i39: Int) =>\n val box41 = coll36(i39)\n val l42 = box41.value\n val tuple43 = {(box43: Box) => box43.tokens(0) }(box41)\n allOf(Coll[Boolean](l42 >= coll19(i39).value, l42 >= 2000000L, tuple43._1 == coll28, tuple43._2 == 1L, {(box44: Box) => box44.R4[Coll[Long]].get(0) }(box41) == l32, {(box44: Box) => box44.R4[Coll[Long]].get(1) }(box41) > 0L, blake2b256(box41.propositionBytes) == coll21.slice(4, coll21.size).map({(opt44: Option[Coll[Byte]]) => func5(opt44) })(i39)))\n }), {(coll39: Coll[Byte]) => byteArrayToLong(coll39.slice(8, 16)) }({(box39: Box) => box39.R4[Coll[AvlTree]].get(0) }(box37).get(coll38, coll20(3)).get) >= func9((coll21(2), (0L, ({(box39: Box) => box39.R5[Coll[Long]].get(1) }(box37) / 2L, 0L)))), {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.exists({(box41: Box) => box41.tokens.exists({(tuple43: (Coll[Byte], Long)) => tuple43._1 == tuple39._2 }) }) }((OUTPUTS, coll38))))\n )} else { false } }(b10), {(b13: Byte) => if (b13 == 7.toByte) { {(tuple15: (Coll[Byte], Box)) => if (i11 >= OUTPUTS.size) { false } else {(\n val box17 = OUTPUTS(i11)\n val l18 = box17.value\n val l19 = SELF.value\n val coll20 = box17.propositionBytes\n val coll21 = SELF.bytesWithoutRef\n val coll22 = SELF.propositionBytes\n val i23 = SELF.creationInfo._1\n val coll24 = box17.bytesWithoutRef\n val i25 = box17.creationInfo._1\n allOf(Coll[Boolean](l18 >= l19 - 2000000L, blake2b256(coll20) == func5(func3(tuple15._2).getMany(Coll[Coll[Byte]](tuple15._1), getVar[Coll[Byte]](1.toByte).getOrElse(Coll[Byte]()))(0)), coll21.slice(func12(l19) + coll22.size + func12(i23.toLong), coll21.size) == coll24.slice(func12(l18) + coll20.size + func12(i25.toLong), coll24.size), anyOf(Coll[Boolean](i25 - i23 >= 504000, coll22 != coll20))))\n )} }((coll4, func2((CONTEXT.dataInputs, coll1))(0))) } else { false } }(b10))))\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 1,
"name": "Paideia DAO",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 1,
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},
{
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"index": 2,
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"name": "Paideia Action",
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}
],
"additionalRegisters": {}
},
{
"boxId": "93899ba94e5bc3ff9d735ad1c2b262241753ded528a3da9ca61bde60d195d812",
"value": 993303931723,
"index": 1,
"spendingProof": "7934147978d51cd2b37dd5bb644ffd7202f6f016431df48fcf0bcf7919e5696e35dda4fe06e83a7ec4a33dbb872657b76d731e77e0d1853f",
"outputBlockId": "ff177a905ee4595767d1d59a929f6e01694b7d72c8c9c6e14788b6c82e67fab5",
"outputTransactionId": "613bc64b2c061511c7509809a46aa5b78157e4f8f3d1d92463d61755fafc3937",
"outputIndex": 3,
"outputGlobalIndex": 43412750,
"outputCreatedAt": 1380519,
"outputSettledAt": 1380522,
"ergoTree": "0008cd028ee1019ca83537c95bbfb3d35afac4c16790d3f1597bd75b67e452b4f0d2cb63",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8ee101,cddaf3,...)))}",
"address": "9fbzAZAQauntRwsnCNFPb7DzT7854qWp4uxeWrhgiscW43aFGfN",
"assets": [
{
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},
{
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},
{
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{
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},
{
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{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
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},
{
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},
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},
{
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},
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},
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},
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},
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},
{
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{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "110780a8ad82db64a0f5f9be090200000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1730203200000,1273970000,1,0,0,0,0]"
},
"R6": {
"serializedValue": "1d050180a8d6b90701020180a8d6b90701140114",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[1000000000],[1],[1000000000],[10],[10]]"
},
"R8": {
"serializedValue": "1102a0cda3850200",
"sigmaType": "Coll[SLong]",
"renderedValue": "[273970000,0]"
},
"R7": {
"serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000f956327cd94585c7e7bcd013f6fa45353d3084ed2a471dc8e412f5b38b1d8d0401072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c64022bd2b0110a052dac79e4dced72bced635cdbae99a0ccbafd903437086c8d604f010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "c719b19e0430f57d7d3727fed2e1be4c1a26512ca39d31632c0b37bc215a59ef",
"transactionId": "e2b477d3cb14bd2a06c6469b67d669964fc213628224bbe36f34a96a47bd2b99",
"blockId": "f132ce71b8f450aa8eeface90c0abdc42e94c54ff657b4ef0beb76237b0126c0",
"value": 1000000000,
"index": 0,
"globalIndex": 43413293,
"creationHeight": 1380540,
"settlementHeight": 1380543,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
"ergoTreeScript": "{\n val coll1 = placeholder[Coll[Byte]](0)\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val func3 = {(box3: Box) => box3.R4[AvlTree].get }\n val coll4 = Coll[Byte](\n 3.toByte, -99.toByte, 42.toByte, 10.toByte, 33.toByte, -115.toByte, 124.toByte, 72.toByte, -56.toByte, -3.toByte, 70.toByte, -88.toByte, -46.toByte, -108.toByte, 49.toByte, -67.toByte, 5.toByte, 108.toByte, -124.toByte, -120.toByte, 42.toByte, 33.toByte, 106.toByte, 86.toByte, 115.toByte, 38.toByte, -61.toByte, -57.toByte, -104.toByte, 78.toByte, -56.toByte, 53.toByte\n )\n val func5 = {(opt5: Option[Coll[Byte]]) => opt5.get.slice(1, 33) }\n val func6 = {(box6: Box) => box6.tokens(0) }\n val func7 = {(box7: Box) => box7.tokens(1) }\n val func8 = {(box8: Box) => box8.tokens(2) }\n val func9 = {(tuple9: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple11 = tuple9._2\n val l12 = tuple11._1\n val tuple13 = tuple11._2\n val l14 = tuple13._1\n val l15 = tuple13._2\n tuple9._1.map({(coll16: Coll[Byte]) => if (coll16.size == 9) {(\n val l18 = byteArrayToLong(coll16.slice(1, 9))\n if (l18 < l12) { l12 } else { if (l18 > l14) { l14 } else { l18 } }\n )} else { l15 } }).getOrElse(l15)\n }\n val b10 = getVar[Byte](0.toByte).get\n val i11 = INPUTS.indexOf(SELF, 0)\n val func12 = {(l12: Long) =>\n if (l12 < 128L) { 1 } else {\n if (l12 < 16384L) { 2 } else {\n if (l12 < 2097152L) { 3 } else {\n if (l12 < 268435456L) { 4 } else {\n if (l12 < 34359738368L) { 5 } else {\n if (l12 < 4398046511104L) { 6 } else { if (l12 < 562949953421312L) { 7 } else { if (l12 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b13: Byte) => if (b13 == 11.toByte) {(\n val box15 = OUTPUTS(0)\n val coll16 = CONTEXT.dataInputs\n val box17 = getVar[Box](2.toByte).get\n val coll18 = box17.propositionBytes\n val coll19 = getVar[Coll[Box]](3.toByte).get\n val coll20 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll21 = func3(func2((coll16, coll1))(0)).getMany(Coll[Coll[Byte]](coll4, Coll[Byte](-16.toByte, 54.toByte, 125.toByte, -33.toByte, 52.toByte, 53.toByte, -104.toByte, 31.toByte, 74.toByte, -91.toByte, 87.toByte, 27.toByte, -111.toByte, -35.toByte, 70.toByte, -2.toByte, -127.toByte, 54.toByte, 103.toByte, -14.toByte, -120.toByte, -115.toByte, 79.toByte, -58.toByte, -111.toByte, -106.toByte, -113.toByte, -34.toByte, 21.toByte, -121.toByte, -101.toByte, -105.toByte), Coll[Byte](88.toByte, 30.toByte, -80.toByte, 92.toByte, -24.toByte, 20.toByte, -36.toByte, 63.toByte, 36.toByte, 121.toByte, -28.toByte, -80.toByte, 2.toByte, 125.toByte, -79.toByte, -59.toByte, 73.toByte, 79.toByte, -28.toByte, 32.toByte, 61.toByte, 117.toByte, -124.toByte, 18.toByte, 101.toByte, -10.toByte, -57.toByte, 82.toByte, -105.toByte, -43.toByte, -20.toByte, -63.toByte), blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 112.toByte, 114.toByte, 111.toByte, 112.toByte, 111.toByte, 115.toByte, 97.toByte, 108.toByte, 46.toByte).append(coll18))).append(coll19.map({(box21: Box) => blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(box21.propositionBytes)) })), coll20(1))\n val tuple22 = func7(box15)\n val tuple23 = func7(SELF)\n val coll24 = tuple23._1\n val l25 = tuple23._2\n val tuple26 = func8(box15)\n val tuple27 = func8(SELF)\n val coll28 = tuple27._1\n val i29 = coll19.size\n val box30 = OUTPUTS(1)\n val l31 = box30.value\n val l32 = 9223372036854775807L - l25\n val tuple33 = {(box33: Box) => box33.tokens(0) }(box30)\n val tuple34 = {(box34: Box) => box34.tokens(1) }(box30)\n val coll35 = box30.propositionBytes\n val coll36 = OUTPUTS.slice(2, i29 + 2)\n val box37 = func2((coll16, placeholder[Coll[Byte]](3)))(0)\n val coll38 = coll20(2)\n allOf(Coll[Boolean](allOf(Coll[Boolean](blake2b256(box15.propositionBytes) == func5(coll21(0)), box15.value >= SELF.value, func6(box15) == func6(SELF), tuple22._1 == coll24, tuple22._2 == l25 - 1L, tuple26._1 == coll28, tuple26._2 == tuple27._2 - i29.toLong, box15.tokens.size == 3)), allOf(Coll[Boolean](l31 >= box17.value, l31 >= 5000000L, {(box39: Box) => box39.R4[Coll[Int]].get(0) }(box30).toLong == l32, tuple33._1 == coll24, tuple33._2 == 1L, tuple34._1 == placeholder[Coll[Byte]](2), tuple34._2 == func9((func3(func2((coll16, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.toByte)), coll20(0))(0), (0L, (100000000000L, 1000L)))), coll35 == coll18, {(box39: Box) => box39.R5[Coll[Long]].get(0) }(box30) >= CONTEXT.preHeader.timestamp + func9((coll21(1), (43200000L, (2626560000L, 86400000L)))), blake2b256(coll35) == func5(coll21(3)), {(box39: Box) => box39.R5[Coll[Long]].get(1) }(box30) == 0L, {(box39: Box) =>\n val coll41 = box39.R5[Coll[Long]].get\n coll41.slice(2, coll41.size)\n }(box30).forall({(l39: Long) => l39 == 0L }))), coll36.indices.forall({(i39: Int) =>\n val box41 = coll36(i39)\n val l42 = box41.value\n val tuple43 = {(box43: Box) => box43.tokens(0) }(box41)\n allOf(Coll[Boolean](l42 >= coll19(i39).value, l42 >= 2000000L, tuple43._1 == coll28, tuple43._2 == 1L, {(box44: Box) => box44.R4[Coll[Long]].get(0) }(box41) == l32, {(box44: Box) => box44.R4[Coll[Long]].get(1) }(box41) > 0L, blake2b256(box41.propositionBytes) == coll21.slice(4, coll21.size).map({(opt44: Option[Coll[Byte]]) => func5(opt44) })(i39)))\n }), {(coll39: Coll[Byte]) => byteArrayToLong(coll39.slice(8, 16)) }({(box39: Box) => box39.R4[Coll[AvlTree]].get(0) }(box37).get(coll38, coll20(3)).get) >= func9((coll21(2), (0L, ({(box39: Box) => box39.R5[Coll[Long]].get(1) }(box37) / 2L, 0L)))), {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.exists({(box41: Box) => box41.tokens.exists({(tuple43: (Coll[Byte], Long)) => tuple43._1 == tuple39._2 }) }) }((OUTPUTS, coll38))))\n )} else { false } }(b10), {(b13: Byte) => if (b13 == 7.toByte) { {(tuple15: (Coll[Byte], Box)) => if (i11 >= OUTPUTS.size) { false } else {(\n val box17 = OUTPUTS(i11)\n val l18 = box17.value\n val l19 = SELF.value\n val coll20 = box17.propositionBytes\n val coll21 = SELF.bytesWithoutRef\n val coll22 = SELF.propositionBytes\n val i23 = SELF.creationInfo._1\n val coll24 = box17.bytesWithoutRef\n val i25 = box17.creationInfo._1\n allOf(Coll[Boolean](l18 >= l19 - 2000000L, blake2b256(coll20) == func5(func3(tuple15._2).getMany(Coll[Coll[Byte]](tuple15._1), getVar[Coll[Byte]](1.toByte).getOrElse(Coll[Byte]()))(0)), coll21.slice(func12(l19) + coll22.size + func12(i23.toLong), coll21.size) == coll24.slice(func12(l18) + coll20.size + func12(i25.toLong), coll24.size), anyOf(Coll[Boolean](i25 - i23 >= 504000, coll22 != coll20))))\n )} }((coll4, func2((CONTEXT.dataInputs, coll1))(0))) } else { false } }(b10))))\n}",
"address": "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",
"assets": [
{
"tokenId": "171c56d1aa54a6709bdadcc0f053e7a786411224a8f40111a6878549a3fae842",
"index": 0,
"amount": 1,
"name": "Paideia DAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0b2061b664725d7570fdfc40de19b554e60952ced7649f4ad4a9ee2c8640f7c3",
"index": 1,
"amount": 9223372036854776000,
"name": "Paideia Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "000653ab0e7fb89bfa221d75bd25aed8b98e0bac66a13aa229caf5855128d33a",
"index": 2,
"amount": 9223372036854776000,
"name": "Paideia Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ddb643c3b7bf8250c10d3389430e23feb1e5f08ea7e6cc461f3f97128c32462b",
"mainChain": true
},
{
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"transactionId": "e2b477d3cb14bd2a06c6469b67d669964fc213628224bbe36f34a96a47bd2b99",
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"index": 1,
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"creationHeight": 1380540,
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"ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
"ergoTreeScript": "{\n val func1 = {(box1: Box) => box1.tokens(0) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.exists({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val preHeader3 = CONTEXT.preHeader\n val b4 = getVar[Byte](0.toByte).get\n val func5 = {(box5: Box) =>\n val coll7 = box5.R5[Coll[Long]].get\n coll7.slice(2, coll7.size)\n }\n val opt6 = getVar[(Int, Long)](10.toByte)\n val tuple7 = (-2, 0L)\n val tuple8 = tuple7\n val tuple9 = opt6.getOrElse(tuple8)\n val i10 = tuple9._1\n val l11 = tuple9._2\n val func12 = {(tuple12: (Coll[Box], Coll[Byte])) => tuple12._1.filter({(box14: Box) => blake2b256(box14.propositionBytes) == tuple12._2 }) }\n val func13 = {(box13: Box) => box13.R4[Coll[Int]].get(0) }\n val func14 = {(box14: Box) => box14.R5[Coll[Long]].get(1) }\n val func15 = {(box15: Box) => box15.R6[AvlTree].get }\n val func16 = {(box16: Box) => box16.R4[Coll[Int]].get(1) }\n val coll17 = placeholder[Coll[Byte]](3)\n val func18 = {(tuple18: (Coll[Box], Coll[Byte])) =>\n tuple18._1.filter({(box20: Box) => box20.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == tuple18._2 }) })\n }\n val func19 = {(box19: Box) => box19.R4[AvlTree].get }\n val func20 = {(tuple20: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple22 = tuple20._2\n val l23 = tuple22._1\n val tuple24 = tuple22._2\n val l25 = tuple24._1\n val l26 = tuple24._2\n tuple20._1.map({(coll27: Coll[Byte]) => if (coll27.size == 9) {(\n val l29 = byteArrayToLong(coll27.slice(1, 9))\n if (l29 < l23) { l23 } else { if (l29 > l25) { l25 } else { l29 } }\n )} else { l26 } }).getOrElse(l26)\n }\n val func21 = {(box21: Box) => box21.R5[Coll[Long]].get(0) }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b22: Byte) =>\n if (b22 == 12.toByte) {\n {(coll24: Coll[Coll[Byte]]) =>\n allOf(\n Coll[Boolean](\n preHeader3.height - SELF.creationInfo._1 > 788400, coll24.forall({(coll26: Coll[Byte]) => !func2((OUTPUTS, coll26)) }), INPUTS.size == 1\n )\n )\n }(Coll[Coll[Byte]](func1(SELF)._1))\n } else { false }\n }(b4), {(b22: Byte) => if (b22 == 13.toByte) {(\n val coll24 = func5(SELF)\n val coll25 = SELF.propositionBytes\n val box26 = func12((OUTPUTS, blake2b256(coll25)))(0)\n val l27 = box26.value\n val l28 = func14(SELF)\n val coll29 = CONTEXT.dataInputs\n val coll30 = Coll[Byte]()\n val coll31 = func19(func18((coll29, placeholder[Coll[Byte]](0)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-10.toByte, -1.toByte, -117.toByte, 114.toByte, 16.toByte, 1.toByte, 85.toByte, 69.toByte, -44.toByte, -77.toByte, -84.toByte, 95.toByte, -58.toByte, 12.toByte, -112.toByte, -128.toByte, -110.toByte, -48.toByte, 53.toByte, -95.toByte, -95.toByte, 97.toByte, 85.toByte, -64.toByte, 41.toByte, -24.toByte, -43.toByte, 17.toByte, 98.toByte, 124.toByte, 122.toByte, 44.toByte), Coll[Byte](-81.toByte, 120.toByte, 91.toByte, 10.toByte, -35.toByte, -128.toByte, 92.toByte, 92.toByte, 49.toByte, -15.toByte, -52.toByte, 58.toByte, 62.toByte, -106.toByte, -56.toByte, -112.toByte, 8.toByte, -3.toByte, 113.toByte, 39.toByte, 50.toByte, 1.toByte, 7.toByte, -93.toByte, 120.toByte, 75.toByte, 127.toByte, 73.toByte, -23.toByte, 86.toByte, 72.toByte, 66.toByte)), getVar[Coll[Byte]](1.toByte).getOrElse(coll30))\n val tuple32 = (1L, (999L, 500L))\n val opt33 = opt6\n val tuple34 = tuple7\n val tuple35 = tuple8\n val tuple36 = tuple9\n val coll37 = func19(func18((coll29, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll30))\n val box38 = func12((OUTPUTS, {(opt38: Option[Coll[Byte]]) => opt38.get.slice(1, 33) }(coll37(1))))(0)\n allOf(Coll[Boolean]((coll24.indices.forall({(i39: Int) => if (i39 == i10) { coll24(i39) == l11 } else { coll24(i39) <= l11 } }) && (coll24.size > i10)) && (i10 >= 0), allOf(Coll[Boolean](box26.propositionBytes == coll25, l27 >= SELF.value - 3000000L, l27 >= 2000000L, func1(box26) == func1(SELF), func13(box26) == func13(SELF), func14(box26) == l28, func5(box26) == coll24, func15(box26) == func15(SELF), func16(box26) == if ((l28 >= {(box39: Box) => box39.R5[Coll[Long]].get(1) }(func18((coll29, coll17))(0)) * func20((coll31(0), tuple32)) / 1000L) && \n val l39 = l11\n l39 >= l28 * func20((coll31(1), tuple32)) / 1000L\n ) { i10 } else { -2 })), preHeader3.timestamp > func21(SELF), allOf(Coll[Boolean](box38.value >= 1000000L, {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.flatMap({(box41: Box) => box41.tokens }).fold(0L, {(tuple41: (Long, (Coll[Byte], Long))) =>\n val tuple43 = tuple41._2\n tuple41._1 + if (tuple43._1 == tuple39._2) { tuple43._2 } else { 0L }\n }) }((Coll[Box](box38), placeholder[Coll[Byte]](2))) >= min(SELF.tokens(1)._2, byteArrayToLong(coll37(0).get.slice(1, 9))))), func16(SELF) == -1))\n )} else { false } }(b4), {(b22: Byte) => if (b22 == 6.toByte) {(\n val coll24 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll25 = coll24(4)\n val coll26 = coll24(3)\n val coll27 = coll26.indices.slice(0, coll26.size / 8).map({(i27: Int) => byteArrayToLong(coll26.slice(i27 * 8, i27 + 1 * 8)) })\n val l28 = coll27.fold(0L, {(tuple28: (Long, Long)) => tuple28._1 + tuple28._2 })\n val coll29 = SELF.propositionBytes\n val box30 = func12((OUTPUTS, blake2b256(coll29)))(0)\n val l31 = func21(SELF)\n val avlTree32 = func15(SELF)\n val opt33 = avlTree32.get(coll25, coll24(0))\n val bool34 = opt33.isDefined\n val coll35 = coll24(1)\n val coll36 = func5(SELF)\n val coll37 = func5(box30)\n allOf(Coll[Boolean](byteArrayToLong({(box38: Box) => box38.R4[Coll[AvlTree]].get(0) }(func18((INPUTS, coll17))(0)).get(coll25, coll24(2)).get.slice(8, 16)) >= l28, box30.propositionBytes == coll29, box30.value >= SELF.value, box30.tokens == SELF.tokens, func13(box30) == func13(SELF), func16(box30) == func16(SELF), func21(box30) == l31, func15(box30).digest == if (bool34) { avlTree32.update(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get } else { avlTree32.insert(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get }.digest, preHeader3.timestamp < l31, if (bool34) {(\n val coll38 = opt33.get\n val coll39 = coll38.indices.slice(0, coll38.size / 8).map({(i39: Int) => byteArrayToLong(coll38.slice(i39 * 8, i39 + 1 * 8)) })\n allOf(Coll[Boolean](func14(box30) == func14(SELF) - coll39.fold(0L, {(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 }) + l28, coll37 == coll36.zip(coll39.zip(coll27).map({(tuple40: (Long, Long)) => tuple40._2 - tuple40._1 })).map({(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 })))\n )} else { allOf(Coll[Boolean](func14(box30) == func14(SELF) + l28, coll37 == coll36.zip(coll27).map({(tuple38: (Long, Long)) => tuple38._1 + tuple38._2 }))) }, func2((INPUTS, coll25)), coll37 != coll36))\n )} else { false } }(b4)\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "0b2061b664725d7570fdfc40de19b554e60952ced7649f4ad4a9ee2c8640f7c3",
"index": 0,
"amount": 1,
"name": "Paideia Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 1,
"amount": 10000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "10020201",
"sigmaType": "Coll[SInt]",
"renderedValue": "[1,-1]"
},
"R5": {
"serializedValue": "110480b9acc1d864000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1729866600000,0,0,0]"
},
"R6": {
"serializedValue": "644ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R7": {
"serializedValue": "0e1853657420656d697373696f6e20616d6f756e7420746f2030",
"sigmaType": "Coll[SByte]",
"renderedValue": "53657420656d697373696f6e20616d6f756e7420746f2030"
}
},
"spentTransactionId": "61369ca61b24f6fdad8ee726f9384bf578ff78010bcddd6aae45fd380c0dc7e8",
"mainChain": true
},
{
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"transactionId": "e2b477d3cb14bd2a06c6469b67d669964fc213628224bbe36f34a96a47bd2b99",
"blockId": "f132ce71b8f450aa8eeface90c0abdc42e94c54ff657b4ef0beb76237b0126c0",
"value": 2000000,
"index": 2,
"globalIndex": 43413295,
"creationHeight": 1380540,
"settlementHeight": 1380543,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n1: Coll(11,32,97,-74,100,114,93,117,112,-3,-4,64,-34,25,-75,84,-26,9,82,-50,-41,100,-97,74,-44,-87,-18,44,-122,64,-9,-61)",
"ergoTreeScript": "{\n val func1 = {(box1: Box) => box1.tokens(0) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.exists({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val preHeader3 = CONTEXT.preHeader\n val i4 = INPUTS.size\n val coll5 = placeholder[Coll[Byte]](1)\n val func6 = {(tuple6: (Coll[Box], Coll[Byte])) =>\n tuple6._1.filter({(box8: Box) => box8.tokens.exists({(tuple10: (Coll[Byte], Long)) => tuple10._1 == tuple6._2 }) })\n }\n val coll7 = placeholder[Coll[Byte]](0)\n val func8 = {(box8: Box) => box8.R4[AvlTree].get }\n val func9 = {(coll9: Coll[Box]) =>\n coll9.flatMap({(box11: Box) => box11.tokens }).fold(0L, {(tuple11: (Long, (Coll[Byte], Long))) => tuple11._1 + tuple11._2._2 })\n }\n if (getVar[Byte](0.toByte).get == 12.toByte) {\n sigmaProp(\n {(coll10: Coll[Coll[Byte]]) =>\n allOf(Coll[Boolean](preHeader3.height - SELF.creationInfo._1 > 788400, coll10.forall({(coll12: Coll[Byte]) => !func2((OUTPUTS, coll12)) }), i4 == 1))\n }(Coll[Coll[Byte]](func1(SELF)._1))\n )\n } else {(\n val box10 = func6((CONTEXT.dataInputs, coll5))(0)\n val box11 = func6((OUTPUTS, coll7))(0)\n val avlTree12 = func8(box11)\n val box13 = func6((INPUTS, coll7))(0)\n val coll14 = {(box14: Box) => box14.R7[Coll[(Coll[Byte], Coll[Byte])]].get }(SELF)\n val coll15 = {(box15: Box) => box15.R6[Coll[(Coll[Byte], Coll[Byte])]].get }(SELF)\n val coll16 = {(box16: Box) => box16.R5[Coll[Coll[Byte]]].get }(SELF)\n val avlTree17 = if (coll16.size > 0) { func8(box13).remove(coll16, getVar[Coll[Byte]](2.toByte).get).get } else { func8(box13) }\n val avlTree18 = if (coll15.size > 0) { avlTree17.update(coll15, getVar[Coll[Byte]](3.toByte).get).get } else { avlTree17 }\n sigmaProp(\n allOf(\n Coll[Boolean](\n i4 == 2, allOf(\n Coll[Boolean](\n {(box19: Box) => box19.tokens(0) }(box10)._1 == coll5, {(box19: Box) => box19.R4[Coll[Int]].get(0) }(box10).toLong == {(box19: Box) =>\n box19.R4[Coll[Long]].get(0)\n }(SELF), {(box19: Box) => box19.R4[Coll[Int]].get(1) }(box10).toLong == {(box19: Box) => box19.R4[Coll[Long]].get(1) }(SELF)\n )\n ), preHeader3.timestamp >= {(box19: Box) => box19.R4[Coll[Long]].get(3) }(SELF), !func2((OUTPUTS, func1(SELF)._1)), allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == {(opt19: Option[Coll[Byte]]) => opt19.get.slice(1, 33) }(\n avlTree12.getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n -87.toByte, 85.toByte, -114.toByte, 65.toByte, -122.toByte, -53.toByte, -43.toByte, -86.toByte, 87.toByte, 35.toByte, -88.toByte, 82.toByte, -44.toByte, -63.toByte, -36.toByte, 101.toByte, 125.toByte, -98.toByte, -127.toByte, 67.toByte, -126.toByte, -1.toByte, -120.toByte, -115.toByte, 90.toByte, -118.toByte, -20.toByte, 82.toByte, 21.toByte, 49.toByte, 48.toByte, 29.toByte\n )\n ), getVar[Coll[Byte]](1.toByte).get\n )(0)\n ), box11.tokens == box13.tokens, box11.value >= box13.value, avlTree12.digest == if (coll14.size > 0) {\n avlTree18.insert(coll14, getVar[Coll[Byte]](4.toByte).get).get\n } else { avlTree18 }.digest\n )\n ), OUTPUTS.size == 2, func9(INPUTS) == func9(OUTPUTS) + 1L\n )\n )\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "000653ab0e7fb89bfa221d75bd25aed8b98e0bac66a13aa229caf5855128d33a",
"index": 0,
"amount": 1,
"name": "Paideia Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "110502020080b9acc1d86400",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1,1,0,1729866600000,0]"
},
"R5": {
"serializedValue": "1a00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[]"
},
"R6": {
"serializedValue": "0c3c0e0e0120b0b907abafad8dffce2f9f1dfa1535c022dda05366f4fbd27f581d132f4b23f609030000000000000000",
"sigmaType": "Coll[(Coll[SByte], Coll[SByte])]",
"renderedValue": "[[b0b907abafad8dffce2f9f1dfa1535c022dda05366f4fbd27f581d132f4b23f6,030000000000000000]]"
},
"R7": {
"serializedValue": "0c3c0e0e00",
"sigmaType": "Coll[(Coll[SByte], Coll[SByte])]",
"renderedValue": "[]"
}
},
"spentTransactionId": "339e9587dafc530ab9eb03909c453325061cd6ddcd2f99ba3ad8344a92fddb1e",
"mainChain": true
},
{
"boxId": "1f0b609123fa53498daa4674864aaefce5bd22cb4a769775e50e5f4df558c69b",
"transactionId": "e2b477d3cb14bd2a06c6469b67d669964fc213628224bbe36f34a96a47bd2b99",
"blockId": "f132ce71b8f450aa8eeface90c0abdc42e94c54ff657b4ef0beb76237b0126c0",
"value": 1000000,
"index": 3,
"globalIndex": 43413296,
"creationHeight": 1380540,
"settlementHeight": 1380543,
"ergoTree": "0008cd028ee1019ca83537c95bbfb3d35afac4c16790d3f1597bd75b67e452b4f0d2cb63",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8ee101,cddaf3,...)))}",
"address": "9fbzAZAQauntRwsnCNFPb7DzT7854qWp4uxeWrhgiscW43aFGfN",
"assets": [
{
"tokenId": "ff7f67f63681de1dbfa89aca6a1a0daf5b1a6723e199a40ac680da2938d9dd2a",
"index": 0,
"amount": 1,
"name": "Paideia Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "61369ca61b24f6fdad8ee726f9384bf578ff78010bcddd6aae45fd380c0dc7e8",
"mainChain": true
},
{
"boxId": "442c2b7d5d2d4224ad8c947de358669cf2c3b2380206aadd27ce0d01d2e4a9a5",
"transactionId": "e2b477d3cb14bd2a06c6469b67d669964fc213628224bbe36f34a96a47bd2b99",
"blockId": "f132ce71b8f450aa8eeface90c0abdc42e94c54ff657b4ef0beb76237b0126c0",
"value": 500000000,
"index": 4,
"globalIndex": 43413297,
"creationHeight": 1380540,
"settlementHeight": 1380543,
"ergoTree": "0008cd03553448c194fdd843c87d080f5e8ed983f5bb2807b13b45a9683bba8c7bfb5ae8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(553448,8bebb3,...)))}",
"address": "9h7L7sUHZk43VQC3PHtSp5ujAWcZtYmWATBH746wi75C5XHi68b",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "c5f52c20dd1d057d1cda075b9b8126eeb273bc77a137701d8dcaea1bbd7dd78b",
"mainChain": true
},
{
"boxId": "16d48c99dd768589772055886a72253b13876eaa1257ca9051456f57df7121df",
"transactionId": "e2b477d3cb14bd2a06c6469b67d669964fc213628224bbe36f34a96a47bd2b99",
"blockId": "f132ce71b8f450aa8eeface90c0abdc42e94c54ff657b4ef0beb76237b0126c0",
"value": 1850000,
"index": 5,
"globalIndex": 43413298,
"creationHeight": 1380540,
"settlementHeight": 1380543,
"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": "0124dc8e0fa9296c5d99d15f30cb8cfeaa7389bcb17eaf9b5a232ffbe42b814e",
"mainChain": true
},
{
"boxId": "d87558cdef53eaa5fafcd77b94b2797e9f7ca704227c6c227127d70f7a8d3db5",
"transactionId": "e2b477d3cb14bd2a06c6469b67d669964fc213628224bbe36f34a96a47bd2b99",
"blockId": "f132ce71b8f450aa8eeface90c0abdc42e94c54ff657b4ef0beb76237b0126c0",
"value": 992794081723,
"index": 6,
"globalIndex": 43413299,
"creationHeight": 1380540,
"settlementHeight": 1380543,
"ergoTree": "0008cd028ee1019ca83537c95bbfb3d35afac4c16790d3f1597bd75b67e452b4f0d2cb63",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8ee101,cddaf3,...)))}",
"address": "9fbzAZAQauntRwsnCNFPb7DzT7854qWp4uxeWrhgiscW43aFGfN",
"assets": [
{
"tokenId": "f1c0ace46ed88730a270c584df14b5b4383e66ead537aafd51cb63e455ad9e65",
"index": 0,
"amount": 14064755982,
"name": "Ergo_886b7721_LP",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 1,
"amount": 200000000,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "2c6cc91540888dfe3b751e42c52bad6ac3cc6fd91d2e4583be9b465d765cecb7",
"index": 2,
"amount": 1,
"name": "Emerald Gaze Lilith",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 3,
"amount": 1633410256,
"name": "SPF",
"decimals": 6,
"type": "EIP-004"
},
{
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"index": 4,
"amount": 2,
"name": "Scrapper",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 5,
"amount": 1,
"name": "Flutterkin",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 6,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 7,
"amount": 1,
"name": "Restless Nights",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 8,
"amount": 1,
"name": "Data Diver",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 9,
"amount": 1,
"name": "Buster Blader Stan",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 10,
"amount": 9223372036854776000,
"name": "Paideia Action",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 11,
"amount": 1,
"name": "Chelone the Bounded",
"decimals": 0,
"type": "EIP-004"
},
{
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"name": "Iracebeth",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 13,
"amount": 3,
"name": "Techtomb Beetles",
"decimals": 0,
"type": "EIP-004"
},
{
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"type": "EIP-004"
},
{
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"name": "👽🚀",
"decimals": 0,
"type": "EIP-004"
},
{
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"name": "RSV Ram [ERGnomes Sigma Auctions] #RSV01",
"decimals": 0,
"type": "EIP-004"
},
{
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"name": "ERGnomes Loyalty Crypto vs Fiat [70/221]",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 18,
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"name": "GNOMECOIN",
"decimals": 0,
"type": "EIP-004"
},
{
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"amount": 1,
"name": "Spectrum Finance Community Vesting Key",
"decimals": 0,
"type": "EIP-004"
},
{
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"name": "Sigmanaut",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 21,
"amount": 1,
"name": "Prometheus",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 22,
"amount": 100000,
"name": "🚀",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 23,
"amount": 31380347403,
"name": "Ergo_ca0ed009_LP",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "80f27dd0aecfee0bcedd0f2d4a99dc5bda656a108d1a7609cf896553ecb2bf23",
"index": 24,
"amount": 1,
"name": "Gnomekin #1722 ERGnomes Halloween '21 Special",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 25,
"amount": 2328,
"name": "TRUMP 2024",
"decimals": 0,
"type": "EIP-004"
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