Transaction
ID: f03e80daa2...3f1d
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
6.67 ERG
Tokens:
Loading assets...
Outputs (6)
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:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.2 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00185 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
6.46 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 290,746
Total coins transferred: 7.67 ERG
Fees: 0.00185 ERG
Fees per byte: 0.000000209 ERG
Raw Transaction Data
{
"id": "f03e80daa25703ef20ae5ec178488bb6efdda81a2f41198c6d155ce4450b3f1d",
"blockId": "230f690e521ae8119a8b18f791408830c1ebd757f711912cf93d6395b2c11a6a",
"inclusionHeight": 1468555,
"timestamp": 1740425429038,
"index": 4,
"globalIndex": 8628505,
"numConfirmations": 290746,
"inputs": [
{
"boxId": "61bf0e19f46cd68ceca944f85c9fc3571dd3a162cc493eef92cbcca6b522a062",
"value": 1000000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "e3562b06a1aaa22fd1df6eb8297840009cc40b3a4c11429826f16579406033e7",
"outputTransactionId": "66c0cff30896b98419ca593c5cdad5965a2295799a73a5688bded8426a049a29",
"outputIndex": 0,
"outputGlobalIndex": 46005732,
"outputCreatedAt": 1450890,
"outputSettledAt": 1450892,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-105,-14,75,98,10,-11,-112,18,-124,30,119,118,21,-93,55,-12,120,-123,-79,-55,83,-91,46,-57,-99,127,45,-52,-39,-104,-24,100)\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(-8,76,14,-96,114,-95,13,-96,-85,4,-64,22,-107,-35,-83,63,-115,68,-31,37,-4,35,-116,-102,-2,-116,4,-125,-27,16,108,-56)",
"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": "685065346a3665873115d64aadfe82e10f07cfdc526148802aa3e0f5bcd2c4ad",
"index": 1,
"amount": 9223372036854776000,
"name": "Sigmanauts Mining DAO Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fad4c073aa6aa6e4e5e442f2a22cba81f24a7d1a1c165aafd3fe7343cd84ddad",
"index": 2,
"amount": 9223372036854776000,
"name": "Sigmanauts Mining DAO Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "fe4108bcb9433d4ee51d4fa363065f1418ebcd1915a413965fa4c11a9fe666f1",
"value": 1000000,
"index": 1,
"spendingProof": "db64b941d7800ed367dbc86fca01e035989f870327ac08b5583c77117829397f7f5faf7eadc0b2a6b9d753c8e9ce18137b46ed9a0f2fe0c5",
"outputBlockId": "a90b976738a125445fd16c61b865819408297a8807af4169fa04928e2da6ead8",
"outputTransactionId": "eb8940e79263ef6769ef506d7f0e43d51684558b1c7d841d64ca55f7bda885b7",
"outputIndex": 3,
"outputGlobalIndex": 46330199,
"outputCreatedAt": 1464287,
"outputSettledAt": 1464289,
"ergoTree": "0008cd028c945947b43157d9006ba85e05cddea5b527a9af821eacb2eb9e8fc55af6fd36",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8c9459,aa05aa,...)))}",
"address": "9fayRrb8wGmJcCHMg1phwzCTaLf3sZAX7BiJrQhPFUAshceX71u",
"assets": [
{
"tokenId": "87095cd8640c37893e25dbe4f67dbd8b2564298b7666ec44b0f207d855448b6a",
"index": 0,
"amount": 1,
"name": "Walrus DAO Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "9cb921a7a337eca5944794b771d2a8ea19efdab1493c5ddb3bc1dacdc260e41b",
"value": 6666209814,
"index": 2,
"spendingProof": "4a152685337f0d33dfcd229b06bc1648fe5558470ad78095ef80f2c5954ab0aaa73401cc8af46ede42a049d2b549d0a7707b78b9e3bb99b9",
"outputBlockId": "a90b976738a125445fd16c61b865819408297a8807af4169fa04928e2da6ead8",
"outputTransactionId": "eb8940e79263ef6769ef506d7f0e43d51684558b1c7d841d64ca55f7bda885b7",
"outputIndex": 6,
"outputGlobalIndex": 46330202,
"outputCreatedAt": 1464287,
"outputSettledAt": 1464289,
"ergoTree": "0008cd028c945947b43157d9006ba85e05cddea5b527a9af821eacb2eb9e8fc55af6fd36",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8c9459,aa05aa,...)))}",
"address": "9fayRrb8wGmJcCHMg1phwzCTaLf3sZAX7BiJrQhPFUAshceX71u",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 190592000,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "c0d9e581c1099455f13b82e13a1c20c7308a736cf63acc1025ae1e17a58a72c9",
"index": 1,
"amount": 1,
"name": "Sigmanauts Mining DAO Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "7bf16bf22db6048fd2730f6de921ea71a312c3962850e6b54f86615264086112",
"index": 2,
"amount": 1,
"name": "DevDAO Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fcfca7654fb0da57ecf9a3f489bcbeb1d43b56dce7e73b352f7bc6f2561d2a1b",
"index": 3,
"amount": 13867615000,
"name": "ErgOne",
"decimals": 8,
"type": "EIP-004"
},
{
"tokenId": "34d449dc84a27d0f8fb2166d415a7223604f6426fb2d83ee099f2312182d575d",
"index": 4,
"amount": 48860790054209,
"name": "PHP",
"decimals": 8,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 5,
"amount": 25000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "a650291cd343d511a435b8720476736fcaf3e6c87f977b4e8123bcff666543be",
"index": 6,
"amount": 35,
"name": "Ergo DevDAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3503ba6ce5d8bc1332229284c95fff15cf3c1d0b463fdfd6f3c9b57b7af09fe3",
"index": 7,
"amount": 1,
"name": "Good Things DAO Token",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "d577aa18ae22a1667f5509796de26b64bc4964407db10e80ee2d1b05f2bdf091",
"index": 8,
"amount": 1,
"name": "Sigmanauts Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "0cca9016769f0abbd704bc14e422ba3dd4ec10e00ecd120f36846bb859a16ca0",
"value": 1000000000,
"index": 0,
"outputBlockId": "4c8dc2ed20f330c612719316b3494a4d66de5f0668ecbc6283a0e3bde4207893",
"outputTransactionId": "66b181ec5489107a9bf3c7b13563acee0d31cd0e79d9b837e2a489467dde6f9a",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64a1db138991f9e426fe847dbae52abd772f8681deb022a8a3d0cad0ef86436f7107072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "21b87abc1710cc5297692c3633c7d0ebe5ad2ed0d06da9bcd763e0c90125b00d",
"value": 1000000000,
"index": 1,
"outputBlockId": "e3562b06a1aaa22fd1df6eb8297840009cc40b3a4c11429826f16579406033e7",
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"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "6461f57ca48e4306a5fbb82d3d4d88a6213fe66d7f38542f0fcab1227c4104ee7a06072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "925249ded9bf6ca2580284a0510d032a680e68dc5b7cde32a732feb3973adc6f",
"value": 1000000000,
"index": 2,
"outputBlockId": "8f371ebc8683986bcad15b26e39a2b58c0c88a807917cb6899f521318b7e790b",
"outputTransactionId": "1d6eea46f873521d899e2ffa3b702d9a474d9ea275791fe62b279dd1013446d2",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "1107c281eacf9d65101000000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1739142807649,8,8,0,0,0,0]"
},
"R6": {
"serializedValue": "1d0501000100010001000100",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[0],[0],[0],[0],[0]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
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"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "e6e4402d54dbb7898110c79e956f3c4b9c712182387fe9722bd077d262c15a4b",
"transactionId": "f03e80daa25703ef20ae5ec178488bb6efdda81a2f41198c6d155ce4450b3f1d",
"blockId": "230f690e521ae8119a8b18f791408830c1ebd757f711912cf93d6395b2c11a6a",
"value": 1000000000,
"index": 0,
"globalIndex": 46470531,
"creationHeight": 1468552,
"settlementHeight": 1468555,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-105,-14,75,98,10,-11,-112,18,-124,30,119,118,21,-93,55,-12,120,-123,-79,-55,83,-91,46,-57,-99,127,45,-52,-39,-104,-24,100)\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(-8,76,14,-96,114,-95,13,-96,-85,4,-64,22,-107,-35,-83,63,-115,68,-31,37,-4,35,-116,-102,-2,-116,4,-125,-27,16,108,-56)",
"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": "685065346a3665873115d64aadfe82e10f07cfdc526148802aa3e0f5bcd2c4ad",
"index": 1,
"amount": 9223372036854776000,
"name": "Sigmanauts Mining DAO Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fad4c073aa6aa6e4e5e442f2a22cba81f24a7d1a1c165aafd3fe7343cd84ddad",
"index": 2,
"amount": 9223372036854776000,
"name": "Sigmanauts Mining DAO Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "72ea9a203e1b47011d2b4fa31f9dc130ce551f1cf261102b82fdac2a6d1708d6",
"mainChain": true
},
{
"boxId": "87c8f12648c3a8b5e2ab10b0ced04d388a61815f96da49bef5f7592c44a272fb",
"transactionId": "f03e80daa25703ef20ae5ec178488bb6efdda81a2f41198c6d155ce4450b3f1d",
"blockId": "230f690e521ae8119a8b18f791408830c1ebd757f711912cf93d6395b2c11a6a",
"value": 5000000,
"index": 1,
"globalIndex": 46470532,
"creationHeight": 1468552,
"settlementHeight": 1468555,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-105,-14,75,98,10,-11,-112,18,-124,30,119,118,21,-93,55,-12,120,-123,-79,-55,83,-91,46,-57,-99,127,45,-52,-39,-104,-24,100)\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(-8,76,14,-96,114,-95,13,-96,-85,4,-64,22,-107,-35,-83,63,-115,68,-31,37,-4,35,-116,-102,-2,-116,4,-125,-27,16,108,-56)",
"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": "2HqXK779y5WmKUAoPJ3tvutbEfrzAptNnHv5xQKPqA14CaX1zvds5pA7ATHAwfqZNcrmaBteieqigARnDDfJn8YNA1oup2KESZUFRVhhfLW4Xrm8cEzKXLRhtgdtmDBy96msvB8wjhAb5KHHQxEu364UZ95X8z3GDxHvAE7no6StVB6P8LuTPWE74PCdqu7cNtx5vnH5U8TvmZjXfpNziv61oKo3mrqe3mvj5wJKgUALWsnr47rSh6ycJXn1rrdGQ9cst2BUneFuCDfHKbd7aBCWLofFcghUrbX9HHQx74mkdrsKsCRwPTkLDH3JqoW3BcVEQhdjWL3hLBf9mTcmfVYjHikbnccPkf8SQjyV4bg6PEbDb7b3i56NmtsYX9T5ddDRXRr8HcKdjFEVRL1d3HWNEPWsSS5yVXn1Ret7SSMijixKWWH74o2jz2f96KRU63c1smKKoK3JTEyFU7drVEK15q2kscVmE3GsPBEt5UuYzsaaU5tb8LZN3brbrEAw2dDvjn4JsfJVeHqDCghtTCMzdkqyZxNetAg6EFCPMEuKhKvjVgqF28RqrYRhNzNUtkgLJ6avpn8DmdrY9hEcMHGqt7DvYDy7zaPVKLruvRDptSXR1r5ojphQm3VBeqkN8J27mRCUAmhvChwu2bZnm8p7WN5DSTc3zc3iLSk7Jkg6XEHCgxdZJoPBiUkzcUrfbHDCegSZ9YChJeoTMF7Nwzqr2qtpivHzKC5z4d4F88ohtmdJzFbMH4ax7JzWFCBQV8mKJDY2azzrrwP7TWFnRG7UgXsqQSRVApELg5bwz6wWD3arZLVKmQvBEDTXvH7WfgxGBf4nmMhVyTAvNzg7X3VvNd5mr49Udnnnh1S6Vi126YrLPL9SzYS1bakUCkkSsjWEhNfoftLpriUQw9zAVoSoRnXJkRDi6ghCuZNZrmpmifZPjFFThQDVUVyRcJSQyGwem4CUbZMXqkN8K6eebw5oNA5RqQVTqejZyfGz4M82aK5f6S7tjQTK1EV12LkukZh4qFxFkBUxhM5SoY9TriygDBtcZF3viUv44diwYYESdwsEsK4RzWW7wdbbHcayM2qhiWLkuSPXC2S6fdy9YZC5k8CG4GPW6wRwGGgbqRpvsHpvh6JQ3dXVbM1xGQfUUZYnTRVbPhTFXTPbA5zfuuSTVnVoAKA3bxHQgobNXXEnj8NB8fXXiXvVeAgaicVWQDVhAEaP1kb9GZwpAJcW55kxvhmzaxCDLnRfrPUc8hRKDDcvShzRX4LjPsjxKYkL4TeT3PbfcmHZGLGJmmiqzZKWRFGWbBg1oZyPP5PUDdRWbCyFB2pJ9z55k6iZQmrY8GobuxV9xQvgijwBxwXSxZHsALK8oLqWd2krkyy9vZNMHe2k8Jw53jtddT4jjJcheZDDheq134mzW5zVgNRyttK7q96iy8AzBig7ivHTTd6jEKMwpPt6oFHdSQPf3p42rNzpVAfg4NPJEiCMCcPtXBs5ftj62zuU66rP354UJ35dfpQ6FSkM3cYyoT41upvB9Uup5MbP1kgS6Y8cuqVfubqMsckRMFceYGJsnJD1LHkAn6LHFpKc7GQXJpGtiuPJTqJvtK1Fn2KsUakApNx8JHf9471RUED7RLGvH4uuVhoCGyef33KoLyXDLJokiY1UT12KknjEhEs3ee1fMmLGszLumNAyTJPbkM9KGdSE7TyAFy3t5UhxYDyttNxUXCQWsC5Uj4QWcw2L8vcbgq3zMmnenGV3NG5sZhogeMFq9UHajGNKppw2xjVj5gFMvfWipFNo3ySCf4ELPV1fULMnRvf5mihce7TfzkRcrVYzGd4TovW1Pm6xdC2DrRDjtyTUz6JZ9huAgSVuYuhewbRXTJy8rqXbrYyTGwZWtEFNJG88BYsorFYieZEGdsfqiSQ3CYt5PmFoFbsobRAkFrodkAh3rwrVwZ31c1XmVocTvnhJAW4ysW9wLzspVbe19Z8sxupLPe29jTT2HZWvGwQbc6y6n6AMVQgRvZJdLEepL9SSHtjLmAtDiiZDbyAuX7UpuAgBngrWLqJepFbBJbUvR7JzGSNSGoSbdV9PqXFSQa8UNdoSNKZtJA6r2pr2H6vo1Txfq1VoPQcLZ4YizQdzaQ8CHj9gdsFV76kSTmFFSj9h16etm2kpMwu7ss2EGuoXEaoYwScGUewK76jxQDHi6xFyeK5eRmpJJkxPXghKphq33z127jB6UkdGP1ECk4PVusEPYdaQpVeQqPSG7cfxr2TZra56QkR4VHe1jYk6R6isKAdF9XfQcqtQA3BzGJayHNjrAMsLnkd4nuRmEn28v46j5z3hjpLEJ81ptrTrdtxtA6tsAdhaHpsgQ1xKSLv4igFyzPSxMkyKxcrR1iCMMKtSajWByKVJy1AD5NDAXKaXK8GdMDMrrZsa31RAFPTMni55igppg1QaWwRdQ2fyEan7ugvBxYqkVrvKh6fiVm96h9DoBQZnMC5F8C9Jv9VXL3t8rPmi9qaEg3k3md7XmVqmR2dwYeRmGsfLDEjYrANKn4hgHBx1MaAjkz2BuFnzXNfiFUYrNEZq7BsRVaZ7JH25MPjEDFKhcqNi5ZxmxXUh9p9dF338Rz69XnocYrde6fwSpqX9PjbqMQ1y6DGSSH3ERNqBt1ZnGfLSZ8bgew8dx7fmwwDdfiA3FR",
"assets": [
{
"tokenId": "685065346a3665873115d64aadfe82e10f07cfdc526148802aa3e0f5bcd2c4ad",
"index": 0,
"amount": 1,
"name": "Sigmanauts Mining DAO Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 1,
"amount": 5000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "10020001",
"sigmaType": "Coll[SInt]",
"renderedValue": "[0,-1]"
},
"R5": {
"serializedValue": "1104f890cfd8ab65000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1741031072828,0,0,0]"
},
"R6": {
"serializedValue": "644ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R7": {
"serializedValue": "0e265265696d62757273652043616e6e6f6e5120666f722044414f205365742d757020436f737473",
"sigmaType": "Coll[SByte]",
"renderedValue": "5265696d62757273652043616e6e6f6e5120666f722044414f205365742d757020436f737473"
}
},
"spentTransactionId": "988ea16de22f956d44c20c9e0e85375e7046367c2920a4ee7ccefc651ce3bce6",
"mainChain": true
},
{
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"transactionId": "f03e80daa25703ef20ae5ec178488bb6efdda81a2f41198c6d155ce4450b3f1d",
"blockId": "230f690e521ae8119a8b18f791408830c1ebd757f711912cf93d6395b2c11a6a",
"value": 1000000,
"index": 2,
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