Transaction
ID: d88ec96a86...5cf2
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
6.18 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
20 ERG
Tokens:
Loading assets...
Outputs (6)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00235 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
26.12 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 91,918
Total coins transferred: 27.18 ERG
Fees: 0.00235 ERG
Fees per byte: 0.000000461 ERG
Raw Transaction Data
{
"id": "d88ec96a861e28d9839a77c145c28772fe1147fda3e49df6d280f797c3135cf2",
"blockId": "f75aa698216f4b8ece0c15cdab1cdfd06c130f45a7d208666c63149b6dbca51e",
"inclusionHeight": 1683532,
"timestamp": 1766450585468,
"index": 4,
"globalIndex": 10012963,
"numConfirmations": 91918,
"inputs": [
{
"boxId": "feb65a42336c29526e0f50ad15b2db68994a9689b87b868a6b0c90519a99317e",
"value": 1000000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "12f1c549f70d4650194db2da03648ea5698701adaa0735e9ff41884995a3b54d",
"outputTransactionId": "f824512e76063a6e2a546c6242cbbb2653fb9e475bfb05abe5aa970d8c22c1f2",
"outputIndex": 0,
"outputGlobalIndex": 52444949,
"outputCreatedAt": 1683511,
"outputSettledAt": 1683513,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)",
"ergoTreeScript": "{\n val coll1 = Coll[Byte](\n -34.toByte, -82.toByte, -49.toByte, 91.toByte, 100.toByte, -70.toByte, -42.toByte, -11.toByte, 87.toByte, 11.toByte, -83.toByte, 10.toByte, 97.toByte, 12.toByte, 78.toByte, 72.toByte, 73.toByte, 87.toByte, -49.toByte, 71.toByte, -126.toByte, 48.toByte, -124.toByte, 0.toByte, -68.toByte, -112.toByte, 64.toByte, 76.toByte, 29.toByte, 20.toByte, 16.toByte, -38.toByte\n )\n val func2 = {(box2: Box) => box2.R4[AvlTree].get }\n val func3 = {(tuple3: (Coll[Box], Coll[Byte])) =>\n tuple3._1.filter({(box5: Box) => box5.tokens.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == tuple3._2 }) })\n }\n val box4 = func3((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)\n val opt5 = getVar[Coll[Byte]](1.toByte)\n val func6 = {(opt6: Option[Coll[Byte]]) => opt6.get.slice(1, 33) }\n val func7 = {(box7: Box) => box7.tokens(0) }\n val tuple8 = func7(SELF)\n val box9 = func3((OUTPUTS, tuple8._1))(0)\n val func10 = {(box10: Box) => box10.tokens(1) }\n val func11 = {(coll11: Coll[Byte]) =>\n val coll13 = func2(box4).getMany(Coll[Coll[Byte]](coll1, coll11), opt5.get)\n allOf(\n Coll[Boolean](\n {(tuple14: (Coll[Box], Coll[Byte])) => tuple14._1.filter({(box16: Box) => blake2b256(box16.propositionBytes) == tuple14._2 }) }(\n (INPUTS, func6(coll13(1)))\n ).size == 1, {(coll14: Coll[Byte]) =>\n allOf(Coll[Boolean](blake2b256(box9.propositionBytes) == coll14, func7(box9) == tuple8, func10(box9)._1 == func10(SELF)._1))\n }(func6(coll13(0)))\n )\n )\n }\n val b12 = getVar[Byte](0.toByte).get\n val i13 = INPUTS.indexOf(SELF, 0)\n val func14 = {(l14: Long) =>\n if (l14 < 128L) { 1 } else {\n if (l14 < 16384L) { 2 } else {\n if (l14 < 2097152L) { 3 } else {\n if (l14 < 268435456L) { 4 } else {\n if (l14 < 34359738368L) { 5 } else {\n if (l14 < 4398046511104L) { 6 } else { if (l14 < 562949953421312L) { 7 } else { if (l14 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b15: Byte) =>\n if (b15 == 0.toByte) {\n func11(\n Coll[Byte](\n 3.toByte, -110.toByte, 8.toByte, -68.toByte, 78.toByte, -17.toByte, -102.toByte, 3.toByte, -24.toByte, -41.toByte, -117.toByte, -122.toByte, 99.toByte, -93.toByte, 1.toByte, -69.toByte, 95.toByte, -83.toByte, -36.toByte, -89.toByte, -117.toByte, -31.toByte, -99.toByte, 127.toByte, -27.toByte, 53.toByte, -77.toByte, -58.toByte, 76.toByte, -66.toByte, -2.toByte, 66.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 2.toByte) {\n func11(\n Coll[Byte](\n -117.toByte, -57.toByte, -113.toByte, 28.toByte, 106.toByte, -82.toByte, -55.toByte, 30.toByte, 98.toByte, -114.toByte, 21.toByte, -49.toByte, 102.toByte, -116.toByte, 22.toByte, -52.toByte, 30.toByte, -101.toByte, -40.toByte, -28.toByte, -71.toByte, -73.toByte, -31.toByte, 109.toByte, 99.toByte, 24.toByte, -75.toByte, -11.toByte, 35.toByte, -91.toByte, -23.toByte, -67.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 1.toByte) {\n func11(\n Coll[Byte](\n -120.toByte, 48.toByte, 97.toByte, 44.toByte, 82.toByte, 53.toByte, 95.toByte, 111.toByte, 40.toByte, 13.toByte, 18.toByte, -105.toByte, -15.toByte, -97.toByte, 103.toByte, -80.toByte, 120.toByte, -55.toByte, -38.toByte, -89.toByte, -41.toByte, -80.toByte, 75.toByte, 69.toByte, -100.toByte, -111.toByte, -52.toByte, 100.toByte, 73.toByte, 87.toByte, -62.toByte, -128.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 3.toByte) {\n func11(\n Coll[Byte](\n 79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 4.toByte) {\n func11(\n Coll[Byte](\n -119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 5.toByte) {\n func11(\n Coll[Byte](\n 58.toByte, 17.toByte, -107.toByte, 92.toByte, 71.toByte, 25.toByte, -27.toByte, -120.toByte, -68.toByte, -26.toByte, -89.toByte, 97.toByte, 29.toByte, 39.toByte, -67.toByte, 31.toByte, -33.toByte, -37.toByte, 87.toByte, 56.toByte, 92.toByte, -82.toByte, -30.toByte, 102.toByte, -40.toByte, 4.toByte, 12.toByte, -119.toByte, 79.toByte, 28.toByte, 46.toByte, 29.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 6.toByte) {\n func11(\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) => if (b15 == 7.toByte) { {(tuple17: (Coll[Byte], Box)) => if (i13 >= OUTPUTS.size) { false } else {(\n val box19 = OUTPUTS(i13)\n val l20 = box19.value\n val l21 = SELF.value\n val coll22 = box19.propositionBytes\n val coll23 = SELF.bytesWithoutRef\n val coll24 = SELF.propositionBytes\n val i25 = SELF.creationInfo._1\n val coll26 = box19.bytesWithoutRef\n val i27 = box19.creationInfo._1\n allOf(Coll[Boolean](l20 >= l21 - 2000000L, blake2b256(coll22) == func6(func2(tuple17._2).getMany(Coll[Coll[Byte]](tuple17._1), opt5.getOrElse(Coll[Byte]()))(0)), coll23.slice(func14(l21) + coll24.size + func14(i25.toLong), coll23.size) == coll26.slice(func14(l20) + coll22.size + func14(i27.toLong), coll26.size), anyOf(Coll[Boolean](i27 - i25 >= 504000, coll24 != coll22))))\n )} }((coll1, box4)) } else { false } }(b12)\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "a7f6d4ccf1288a2b79e3d8741e1e203828135a12b92f8dc4f2d21e40738e0e01",
"index": 0,
"amount": 1,
"name": "Walrus DAO Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "59ee24951ce668f0ed32bdb2e2e5731b6c36128748a3b23c28407c5f8ccbf0f6",
"index": 1,
"amount": 134107,
"name": "WALRUS",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107ca918cdd8465b4af10121aa0a85c0000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1735801275493,134106,9,13,756240,0,0]"
},
"R6": {
"serializedValue": "1d05020000020000020000020000020000",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[0,0],[0,0],[0,0],[0,0],[0,0]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464024ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c64027dceb901cf7945e64d74576a7797fee7e8f3940da9e9e5e8736661eaebe32a38040720005c0c93c45ced569a8786171840f58d3cc2e13e1072a1255c7bb5f46cac689eb603072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "2990c1b32fb92bfeeb8cf733a0ddc322f86f21e2679652f259a7e6f01b18f1fd",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "6e96bbed9688f3d9c67f52925481b7b1447ffca76aa4fece9c4d0ffcf7d34e69",
"outputTransactionId": "5a04474dcc5469f2aa623ad0a04ab6627619d1ecc898904e2241f3c35c15ffa0",
"outputIndex": 1,
"outputGlobalIndex": 51276543,
"outputCreatedAt": 1646886,
"outputSettledAt": 1646888,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)\n1: Coll(-89,-10,-44,-52,-15,40,-118,43,121,-29,-40,116,30,30,32,56,40,19,90,18,-71,47,-115,-60,-14,-46,30,64,115,-114,14,1)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) =>\n tuple1._1.filter({(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == tuple1._2 }) })\n }\n val coll2 = placeholder[Coll[Byte]](1)\n val box3 = func1((OUTPUTS, coll2))(0)\n val box4 = func1((INPUTS, coll2))(0)\n val func5 = {(box5: Box) =>\n val coll7 = box5.tokens\n coll7.slice(2, coll7.size)\n }\n val func6 = {(box6: Box) => box6.R4[Coll[AvlTree]].get(1) }\n val func7 = {(box7: Box) => box7.R5[Coll[Long]].get(0) }\n val func8 = {(box8: Box) => box8.R5[Coll[Long]].get(3) }\n val func9 = {(box9: Box) => box9.R5[Coll[Long]].get(4) }\n val func10 = {(box10: Box) =>\n val coll12 = box10.R5[Coll[Long]].get\n coll12.slice(5, coll12.size)\n }\n val func11 = {(box11: Box) => box11.R6[Coll[Coll[Long]]].get }\n val func12 = {(box12: Box) => box12.R7[Coll[(AvlTree, AvlTree)]].get }\n val func13 = {(box13: Box) => box13.R8[Coll[Long]].get }\n val coll14 = INPUTS(0).id\n val coll15 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val tuple16 = coll15(0)\n val coll17 = tuple16._2\n val l18 = {(coll18: Coll[Byte]) => byteArrayToLong(coll18.slice(8, 16)) }(coll17)\n val func19 = {(box19: Box) => box19.tokens(1) }\n val func20 = {(box20: Box) => box20.R5[Coll[Long]].get(1) }\n val func21 = {(box21: Box) => box21.R4[Coll[AvlTree]].get(0) }\n val func22 = {(box22: Box) => box22.R5[Coll[Long]].get(2) }\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n box3.value >= box4.value, func5(box3) == func5(box4), func6(box3) == func6(box4), func7(box3) == func7(box4), func8(box3) == func8(box4), func9(\n box3\n ) == func9(box4), func10(box3) == func10(box4), func11(box3) == func11(box4), func12(box3) == func12(box4), func13(box3) == func13(box4)\n )\n ), coll14 == tuple16._1, {(tuple23: (Coll[Box], Coll[Byte])) =>\n tuple23._1.flatMap({(box25: Box) => box25.tokens }).fold(0L, {(tuple25: (Long, (Coll[Byte], Long))) =>\n val tuple27 = tuple25._2\n tuple25._1 + if (tuple27._1 == tuple23._2) { tuple27._2 } else { 0L }\n })\n }((OUTPUTS, coll14)) == 1L, (l18 == func19(box3)._2 - func19(box4)._2) && (l18 == func20(box3) - func20(box4)), coll15.size == 1, func21(box4).insert(\n coll15, getVar[Coll[Byte]](2.toByte).get\n ).get.digest == func21(box3).digest, {(coll23: Coll[Byte]) => coll23.slice(0, coll23.size - 16 / 8).indices.map({(i25: Int) =>\n val i27 = i25 * 8\n byteArrayToLong(coll23.slice(i27 + 16, i27 + 8 + 16))\n }) }(coll17).forall({(l23: Long) => l23 == 0L }), {(tuple23: (Coll[Box], Coll[Byte])) =>\n tuple23._1.filter({(box25: Box) => blake2b256(box25.propositionBytes) == tuple23._2 })\n }(\n (\n OUTPUTS, {(opt23: Option[Coll[Byte]]) => opt23.get.slice(1, 33) }(\n {(box23: Box) => box23.R4[AvlTree].get }(func1((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n 3.toByte, -110.toByte, 8.toByte, -68.toByte, 78.toByte, -17.toByte, -102.toByte, 3.toByte, -24.toByte, -41.toByte, -117.toByte, -122.toByte, 99.toByte, -93.toByte, 1.toByte, -69.toByte, 95.toByte, -83.toByte, -36.toByte, -89.toByte, -117.toByte, -31.toByte, -99.toByte, 127.toByte, -27.toByte, 53.toByte, -77.toByte, -58.toByte, 76.toByte, -66.toByte, -2.toByte, 66.toByte\n )\n ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n )\n )(0).value >= SELF.value, func22(box4) + 1L == func22(box3), {(coll23: Coll[Byte]) => byteArrayToLong(coll23.slice(0, 8)) }(coll17) == 0L, l18 > 0L\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "7ec689b43d3cb1da349d68a82702f39d8b6faf2d673a39eff4cb75b9e18b2504",
"value": 6176094581,
"index": 2,
"spendingProof": "fdd5d233864707ca3dd65331a129653b4fb38113ae6a9151db960e70d709f3945928cb3c729a4119466324a8261f3ed88a792a75eb6ef4f0",
"outputBlockId": "557827df3d59d865245202bc89f3d24f9759d0fd93731e25eff28d2e144203d5",
"outputTransactionId": "9354243cdb49919901631ceffab0a9eefdd24bab32256129ff32d71d903358e0",
"outputIndex": 2,
"outputGlobalIndex": 52445316,
"outputCreatedAt": 1683524,
"outputSettledAt": 1683525,
"ergoTree": "0008cd02d3830798ad2e2e0343f06d54d2672a36745f613558d9bd87785e51722ecba86b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d38307,1f1526,...)))}",
"address": "9g8DJQh5kZF8faEDtyqyVX5bwjqmCPu4p5QvEuoGMVHgAhoeCWr",
"assets": [
{
"tokenId": "884153a90d0caf9630ae68e0509dbf6325c23117665c3dd4abdb4aecc707bd28",
"index": 0,
"amount": 1,
"name": "Sigmanauts Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 1,
"amount": 90354000,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "e2c53d59691aa67d52ac256b6ff72ec901553caf08a51a7053ef7c7df59af62a",
"index": 2,
"amount": 1,
"name": "ErgoHack VIII DAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "6ef0423fa6840de2f921e08c9698baaf9b84d34612db9e507f5b4033425ed7a7",
"index": 3,
"amount": 251050000,
"name": "BEPOS",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "837bc17349093984f9b91a59d9a331940c4f521be531a0a3c7bb82dda3a322f9",
"index": 4,
"amount": 999986,
"name": "GraymanCan",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "e49fe717b7ce0f401ba0d3cc9c1b8c6cfd8d2b92ebb69458d9e3adbdb9258a10",
"index": 5,
"amount": 1,
"name": "Sigmanauts Mining DAO Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 6,
"amount": 200000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "3503ba6ce5d8bc1332229284c95fff15cf3c1d0b463fdfd6f3c9b57b7af09fe3",
"index": 7,
"amount": 1,
"name": "Good Things DAO Token",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "d31a913c625e83984201c26799f88ea09fe3e1b79f2e13536068a9baa956a348",
"index": 8,
"amount": 1,
"name": "Paideia Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3204f5cea36e3d3628cdc3708bfe55f23309fcfbe56c8d3a0e74a57b583dc921",
"index": 9,
"amount": 1,
"name": "Autolykos Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "e840e3bf0c4a3390d6ad9e3e9bcc14638e649feddcdd8d245f75b9738680fef6",
"index": 10,
"amount": 10,
"name": "LYKOS",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "1776bafaf9253cd48ff7763bd6f65ff66856700bae5d8778cf36bcc5451a55de",
"value": 20000000000,
"index": 3,
"spendingProof": "8d9c28019422c5b6ecb3925f793cc9ea7719c0656f8add52076e6d811200b636dbeaf3b8a8d8d7a6016b33dbec9be88a55e98f859129c03b",
"outputBlockId": "7a6bc8633b6bf61892a0e7c6dc70394b94d5f19ca16aa3e5fd4cdc506c078e72",
"outputTransactionId": "22288fc6c7f6f8e3f6944ae7ff8f8027492efbeaa98c09dd3850a1f2f358c995",
"outputIndex": 0,
"outputGlobalIndex": 52445402,
"outputCreatedAt": 1683526,
"outputSettledAt": 1683528,
"ergoTree": "0008cd02d3830798ad2e2e0343f06d54d2672a36745f613558d9bd87785e51722ecba86b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d38307,1f1526,...)))}",
"address": "9g8DJQh5kZF8faEDtyqyVX5bwjqmCPu4p5QvEuoGMVHgAhoeCWr",
"assets": [
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 0,
"amount": 300000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "59ee24951ce668f0ed32bdb2e2e5731b6c36128748a3b23c28407c5f8ccbf0f6",
"index": 1,
"amount": 12344,
"name": "WALRUS",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "5ba2214a70f0109781353eb6d8729e7d479882a0c3d89f2ebb34a285d88621db",
"value": 1000000000,
"index": 0,
"outputBlockId": "30231635b59a9b6efde43747809e522e5ac8b89f19421bd6d2eb0c9a226d9d96",
"outputTransactionId": "8da1f966022432fd7fc772f5936e1f332d6af56bc0d56f699d90a634c5c5840c",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64053e63a3d34e26878b942de99b097232977483b952ff5ce991342d87a00918b206072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "c5b5a3c620a9281cd51565482c57288f714381ef038f524399a203b6cc1958e0",
"transactionId": "d88ec96a861e28d9839a77c145c28772fe1147fda3e49df6d280f797c3135cf2",
"blockId": "f75aa698216f4b8ece0c15cdab1cdfd06c130f45a7d208666c63149b6dbca51e",
"value": 1000000000,
"index": 0,
"globalIndex": 52445484,
"creationHeight": 1683531,
"settlementHeight": 1683532,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)",
"ergoTreeScript": "{\n val coll1 = Coll[Byte](\n -34.toByte, -82.toByte, -49.toByte, 91.toByte, 100.toByte, -70.toByte, -42.toByte, -11.toByte, 87.toByte, 11.toByte, -83.toByte, 10.toByte, 97.toByte, 12.toByte, 78.toByte, 72.toByte, 73.toByte, 87.toByte, -49.toByte, 71.toByte, -126.toByte, 48.toByte, -124.toByte, 0.toByte, -68.toByte, -112.toByte, 64.toByte, 76.toByte, 29.toByte, 20.toByte, 16.toByte, -38.toByte\n )\n val func2 = {(box2: Box) => box2.R4[AvlTree].get }\n val func3 = {(tuple3: (Coll[Box], Coll[Byte])) =>\n tuple3._1.filter({(box5: Box) => box5.tokens.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == tuple3._2 }) })\n }\n val box4 = func3((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)\n val opt5 = getVar[Coll[Byte]](1.toByte)\n val func6 = {(opt6: Option[Coll[Byte]]) => opt6.get.slice(1, 33) }\n val func7 = {(box7: Box) => box7.tokens(0) }\n val tuple8 = func7(SELF)\n val box9 = func3((OUTPUTS, tuple8._1))(0)\n val func10 = {(box10: Box) => box10.tokens(1) }\n val func11 = {(coll11: Coll[Byte]) =>\n val coll13 = func2(box4).getMany(Coll[Coll[Byte]](coll1, coll11), opt5.get)\n allOf(\n Coll[Boolean](\n {(tuple14: (Coll[Box], Coll[Byte])) => tuple14._1.filter({(box16: Box) => blake2b256(box16.propositionBytes) == tuple14._2 }) }(\n (INPUTS, func6(coll13(1)))\n ).size == 1, {(coll14: Coll[Byte]) =>\n allOf(Coll[Boolean](blake2b256(box9.propositionBytes) == coll14, func7(box9) == tuple8, func10(box9)._1 == func10(SELF)._1))\n }(func6(coll13(0)))\n )\n )\n }\n val b12 = getVar[Byte](0.toByte).get\n val i13 = INPUTS.indexOf(SELF, 0)\n val func14 = {(l14: Long) =>\n if (l14 < 128L) { 1 } else {\n if (l14 < 16384L) { 2 } else {\n if (l14 < 2097152L) { 3 } else {\n if (l14 < 268435456L) { 4 } else {\n if (l14 < 34359738368L) { 5 } else {\n if (l14 < 4398046511104L) { 6 } else { if (l14 < 562949953421312L) { 7 } else { if (l14 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b15: Byte) =>\n if (b15 == 0.toByte) {\n func11(\n Coll[Byte](\n 3.toByte, -110.toByte, 8.toByte, -68.toByte, 78.toByte, -17.toByte, -102.toByte, 3.toByte, -24.toByte, -41.toByte, -117.toByte, -122.toByte, 99.toByte, -93.toByte, 1.toByte, -69.toByte, 95.toByte, -83.toByte, -36.toByte, -89.toByte, -117.toByte, -31.toByte, -99.toByte, 127.toByte, -27.toByte, 53.toByte, -77.toByte, -58.toByte, 76.toByte, -66.toByte, -2.toByte, 66.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 2.toByte) {\n func11(\n Coll[Byte](\n -117.toByte, -57.toByte, -113.toByte, 28.toByte, 106.toByte, -82.toByte, -55.toByte, 30.toByte, 98.toByte, -114.toByte, 21.toByte, -49.toByte, 102.toByte, -116.toByte, 22.toByte, -52.toByte, 30.toByte, -101.toByte, -40.toByte, -28.toByte, -71.toByte, -73.toByte, -31.toByte, 109.toByte, 99.toByte, 24.toByte, -75.toByte, -11.toByte, 35.toByte, -91.toByte, -23.toByte, -67.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 1.toByte) {\n func11(\n Coll[Byte](\n -120.toByte, 48.toByte, 97.toByte, 44.toByte, 82.toByte, 53.toByte, 95.toByte, 111.toByte, 40.toByte, 13.toByte, 18.toByte, -105.toByte, -15.toByte, -97.toByte, 103.toByte, -80.toByte, 120.toByte, -55.toByte, -38.toByte, -89.toByte, -41.toByte, -80.toByte, 75.toByte, 69.toByte, -100.toByte, -111.toByte, -52.toByte, 100.toByte, 73.toByte, 87.toByte, -62.toByte, -128.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 3.toByte) {\n func11(\n Coll[Byte](\n 79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 4.toByte) {\n func11(\n Coll[Byte](\n -119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 5.toByte) {\n func11(\n Coll[Byte](\n 58.toByte, 17.toByte, -107.toByte, 92.toByte, 71.toByte, 25.toByte, -27.toByte, -120.toByte, -68.toByte, -26.toByte, -89.toByte, 97.toByte, 29.toByte, 39.toByte, -67.toByte, 31.toByte, -33.toByte, -37.toByte, 87.toByte, 56.toByte, 92.toByte, -82.toByte, -30.toByte, 102.toByte, -40.toByte, 4.toByte, 12.toByte, -119.toByte, 79.toByte, 28.toByte, 46.toByte, 29.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 6.toByte) {\n func11(\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) => if (b15 == 7.toByte) { {(tuple17: (Coll[Byte], Box)) => if (i13 >= OUTPUTS.size) { false } else {(\n val box19 = OUTPUTS(i13)\n val l20 = box19.value\n val l21 = SELF.value\n val coll22 = box19.propositionBytes\n val coll23 = SELF.bytesWithoutRef\n val coll24 = SELF.propositionBytes\n val i25 = SELF.creationInfo._1\n val coll26 = box19.bytesWithoutRef\n val i27 = box19.creationInfo._1\n allOf(Coll[Boolean](l20 >= l21 - 2000000L, blake2b256(coll22) == func6(func2(tuple17._2).getMany(Coll[Coll[Byte]](tuple17._1), opt5.getOrElse(Coll[Byte]()))(0)), coll23.slice(func14(l21) + coll24.size + func14(i25.toLong), coll23.size) == coll26.slice(func14(l20) + coll22.size + func14(i27.toLong), coll26.size), anyOf(Coll[Boolean](i27 - i25 >= 504000, coll24 != coll22))))\n )} }((coll1, box4)) } else { false } }(b12)\n )\n )\n )\n}",
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"name": "Walrus DAO Stake State",
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"type": "EIP-004"
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],
"additionalRegisters": {
"R5": {
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"sigmaType": "Coll[SLong]",
"renderedValue": "[1735801275493,146450,10,13,756240,0,0]"
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"R6": {
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"sigmaType": "Coll[Coll[SLong]]",
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"R8": {
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"renderedValue": null
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{
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"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)\n1: Coll(-89,-10,-44,-52,-15,40,-118,43,121,-29,-40,116,30,30,32,56,40,19,90,18,-71,47,-115,-60,-14,-46,30,64,115,-114,14,1)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) =>\n tuple1._1.filter({(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == tuple1._2 }) })\n }\n val coll2 = placeholder[Coll[Byte]](1)\n val box3 = func1((OUTPUTS, coll2))(0)\n val box4 = func1((INPUTS, coll2))(0)\n val func5 = {(box5: Box) =>\n val coll7 = box5.tokens\n coll7.slice(2, coll7.size)\n }\n val func6 = {(box6: Box) => box6.R4[Coll[AvlTree]].get(1) }\n val func7 = {(box7: Box) => box7.R5[Coll[Long]].get(0) }\n val func8 = {(box8: Box) => box8.R5[Coll[Long]].get(3) }\n val func9 = {(box9: Box) => box9.R5[Coll[Long]].get(4) }\n val func10 = {(box10: Box) =>\n val coll12 = box10.R5[Coll[Long]].get\n coll12.slice(5, coll12.size)\n }\n val func11 = {(box11: Box) => box11.R6[Coll[Coll[Long]]].get }\n val func12 = {(box12: Box) => box12.R7[Coll[(AvlTree, AvlTree)]].get }\n val func13 = {(box13: Box) => box13.R8[Coll[Long]].get }\n val coll14 = INPUTS(0).id\n val coll15 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val tuple16 = coll15(0)\n val coll17 = tuple16._2\n val l18 = {(coll18: Coll[Byte]) => byteArrayToLong(coll18.slice(8, 16)) }(coll17)\n val func19 = {(box19: Box) => box19.tokens(1) }\n val func20 = {(box20: Box) => box20.R5[Coll[Long]].get(1) }\n val func21 = {(box21: Box) => box21.R4[Coll[AvlTree]].get(0) }\n val func22 = {(box22: Box) => box22.R5[Coll[Long]].get(2) }\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n box3.value >= box4.value, func5(box3) == func5(box4), func6(box3) == func6(box4), func7(box3) == func7(box4), func8(box3) == func8(box4), func9(\n box3\n ) == func9(box4), func10(box3) == func10(box4), func11(box3) == func11(box4), func12(box3) == func12(box4), func13(box3) == func13(box4)\n )\n ), coll14 == tuple16._1, {(tuple23: (Coll[Box], Coll[Byte])) =>\n tuple23._1.flatMap({(box25: Box) => box25.tokens }).fold(0L, {(tuple25: (Long, (Coll[Byte], Long))) =>\n val tuple27 = tuple25._2\n tuple25._1 + if (tuple27._1 == tuple23._2) { tuple27._2 } else { 0L }\n })\n }((OUTPUTS, coll14)) == 1L, (l18 == func19(box3)._2 - func19(box4)._2) && (l18 == func20(box3) - func20(box4)), coll15.size == 1, func21(box4).insert(\n coll15, getVar[Coll[Byte]](2.toByte).get\n ).get.digest == func21(box3).digest, {(coll23: Coll[Byte]) => coll23.slice(0, coll23.size - 16 / 8).indices.map({(i25: Int) =>\n val i27 = i25 * 8\n byteArrayToLong(coll23.slice(i27 + 16, i27 + 8 + 16))\n }) }(coll17).forall({(l23: Long) => l23 == 0L }), {(tuple23: (Coll[Box], Coll[Byte])) =>\n tuple23._1.filter({(box25: Box) => blake2b256(box25.propositionBytes) == tuple23._2 })\n }(\n (\n OUTPUTS, {(opt23: Option[Coll[Byte]]) => opt23.get.slice(1, 33) }(\n {(box23: Box) => box23.R4[AvlTree].get }(func1((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n 3.toByte, -110.toByte, 8.toByte, -68.toByte, 78.toByte, -17.toByte, -102.toByte, 3.toByte, -24.toByte, -41.toByte, -117.toByte, -122.toByte, 99.toByte, -93.toByte, 1.toByte, -69.toByte, 95.toByte, -83.toByte, -36.toByte, -89.toByte, -117.toByte, -31.toByte, -99.toByte, 127.toByte, -27.toByte, 53.toByte, -77.toByte, -58.toByte, 76.toByte, -66.toByte, -2.toByte, 66.toByte\n )\n ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n )\n )(0).value >= SELF.value, func22(box4) + 1L == func22(box3), {(coll23: Coll[Byte]) => byteArrayToLong(coll23.slice(0, 8)) }(coll17) == 0L, l18 > 0L\n )\n )\n )\n}",
"address": "2jgvs128ygPbfNoWHfk6xiWjhw1F9itXsBKCWiuieFXxnySNVKuEYrMzsMwJSYTWeSqcEePukgJeXsTWHeW3rq7teNDGyP4FZfTHzn51A5b8KLwWFdXFLGg5jqGWoDSHnxMaPw2PFjBM1Ceh3ELwGt54XNssu6HZ5wdAkHA7PuKb4QeNMPU7gXLfoXYM1Gndtn9zkT9P5z2vcF2oBuE5frRP7Qd8TNMkSFdXYAKmwNA3JMw8MQv65fHRCqNngyA6WgaaHdrqSAHua7kTL7uR9Ux8RoufHN8zZuoUK9xkRo4AAnAcT98LaB5sJtj3fLyTgJnKjbeQC6cKFxZsuoXrumL3SPdfgjYXB1tnSkXFHBEqTfRA55VnNw854vXmH19XsbXucPdAkT4yK1Po8k1GR65d8Jf2Q9YHwWSFnRRpRHgwN4uTYCyhg9gsD5TBro1Bx3qFptXy21XbcK45WbtC4ZcSgH3fZpydf1ab78ZsQhQKUs5RGMQGTakCczXktSqPTnuQARirpvwcaf6ntucUkReXHgbuKMaKN4hU1ayhxBmpJxT9VyBwAntBFdHmK62uNNTBfKxENg4dnVQ3VaWbiuAaKoCWHERRgQVvzwtbKCu5ZfiAuY4JQ8zD6jSAq3xj6krvmtRzqc4Pb1fcWUCZKCpncVTUnLzLxftucqBd5BEiibtJWDDM3fZPNXMxKwrqnTSTA3WT3oR5akg1vmQTRWE6z9yU9U1hurqbPwJ3jRq3Gtb8W6bCeiBRPBzFfcYiEwyQMUbot2N1TNKGQSyDva9U9aV5b8oX3xRbsi5iomoKFgdrfTgvbSZ99Q8iif7P6ZwXGEs26GE6WK7sMyNwTPpGyTVoAXZNgoc1o9XB5kMEwWpUy2v9Cz5oQmNhiBqaM6n9VtjUKPRfU8XMpQ73Tz5eD2pCy7Rg2jxupp1DzKAexrYaiK25kA8xbHCrJe9F1SKC8gQpMBXFrYcXbxo1SWDMeUKpd9FCv25S3ndcD5qmG4HzuoCCJfEuiwvmcEkPEbmEwNdcE44PQpVTpHCFhXksDRdNVZCunYn6BGpm4jFdTdq2mWENdKwHrwgtwn5rU6PofduCiF5DGRDhjgrAoGnKiYE3MNT6BxHP8vkQM1gzZGULJJHDna98EwDpUgiNdSHNbjYw3Pie6qQuWtuuBtogRjHWPQGAE4YNPNAyNbbQQByYs5iP5J39LW5gPQujP6xCg9Jujpto4bXJf51TPsgbiXdBoGj6EFQKyBxdPhK7UyFcBApPziiWb5Cdh5m3qgjL4R7dALBWBXhBA78SesF5kwndBghqUwixNBh",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "cb64177ecb326957aa02286467944e2a6d7b1dd2bbc2b6917d3aa9bd38e35729",
"transactionId": "d88ec96a861e28d9839a77c145c28772fe1147fda3e49df6d280f797c3135cf2",
"blockId": "f75aa698216f4b8ece0c15cdab1cdfd06c130f45a7d208666c63149b6dbca51e",
"value": 1000000,
"index": 2,
"globalIndex": 52445486,
"creationHeight": 1683531,
"settlementHeight": 1683532,
"ergoTree": "0008cd02d3830798ad2e2e0343f06d54d2672a36745f613558d9bd87785e51722ecba86b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d38307,1f1526,...)))}",
"address": "9g8DJQh5kZF8faEDtyqyVX5bwjqmCPu4p5QvEuoGMVHgAhoeCWr",
"assets": [
{
"tokenId": "feb65a42336c29526e0f50ad15b2db68994a9689b87b868a6b0c90519a99317e",
"index": 0,
"amount": 1,
"name": "Walrus DAO Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e1557616c7275732044414f204d656d62657273686970",
"sigmaType": "Coll[SByte]",
"renderedValue": "57616c7275732044414f204d656d62657273686970"
},
"R5": {
"serializedValue": "0e3857616c7275732044414f202d20506f77657265642062792050616964656961202d2068747470733a2f2f6170702e706169646569612e696d",
"sigmaType": "Coll[SByte]",
"renderedValue": "57616c7275732044414f202d20506f77657265642062792050616964656961202d2068747470733a2f2f6170702e706169646569612e696d"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
}
},
"spentTransactionId": "8677bcc5692a427cd7c8443a1656836890ee55f3a3ce7405da785bc3ba6849ef",
"mainChain": true
},
{
"boxId": "ca1452c557fe37d193cbe94da98f10fc5bf8a8aae4ad498acdc7972e21cc959e",
"transactionId": "d88ec96a861e28d9839a77c145c28772fe1147fda3e49df6d280f797c3135cf2",
"blockId": "f75aa698216f4b8ece0c15cdab1cdfd06c130f45a7d208666c63149b6dbca51e",
"value": 50000000,
"index": 3,
"globalIndex": 52445487,
"creationHeight": 1683531,
"settlementHeight": 1683532,
"ergoTree": "0008cd03553448c194fdd843c87d080f5e8ed983f5bb2807b13b45a9683bba8c7bfb5ae8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(553448,8bebb3,...)))}",
"address": "9h7L7sUHZk43VQC3PHtSp5ujAWcZtYmWATBH746wi75C5XHi68b",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "8480737f6e1e13189563b3a0ed926e749b5ec1d1a08527fbbf57e786fbd21d06",
"transactionId": "d88ec96a861e28d9839a77c145c28772fe1147fda3e49df6d280f797c3135cf2",
"blockId": "f75aa698216f4b8ece0c15cdab1cdfd06c130f45a7d208666c63149b6dbca51e",
"value": 2350000,
"index": 4,
"globalIndex": 52445488,
"creationHeight": 1683531,
"settlementHeight": 1683532,
"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": "29f1f1e64a3eb9f8b4580319ee8964d06becc86db1cebb563958f049ef4eccea",
"mainChain": true
},
{
"boxId": "92179dd8aae262d032a7368eb3a95c3edaaa3cc3fd880a889fec83fcf7544d23",
"transactionId": "d88ec96a861e28d9839a77c145c28772fe1147fda3e49df6d280f797c3135cf2",
"blockId": "f75aa698216f4b8ece0c15cdab1cdfd06c130f45a7d208666c63149b6dbca51e",
"value": 26122744581,
"index": 5,
"globalIndex": 52445489,
"creationHeight": 1683531,
"settlementHeight": 1683532,
"ergoTree": "0008cd02d3830798ad2e2e0343f06d54d2672a36745f613558d9bd87785e51722ecba86b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d38307,1f1526,...)))}",
"address": "9g8DJQh5kZF8faEDtyqyVX5bwjqmCPu4p5QvEuoGMVHgAhoeCWr",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 90354000,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "e2c53d59691aa67d52ac256b6ff72ec901553caf08a51a7053ef7c7df59af62a",
"index": 1,
"amount": 1,
"name": "ErgoHack VIII DAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "6ef0423fa6840de2f921e08c9698baaf9b84d34612db9e507f5b4033425ed7a7",
"index": 2,
"amount": 251050000,
"name": "BEPOS",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "837bc17349093984f9b91a59d9a331940c4f521be531a0a3c7bb82dda3a322f9",
"index": 3,
"amount": 999986,
"name": "GraymanCan",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "e49fe717b7ce0f401ba0d3cc9c1b8c6cfd8d2b92ebb69458d9e3adbdb9258a10",
"index": 4,
"amount": 1,
"name": "Sigmanauts Mining DAO Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "884153a90d0caf9630ae68e0509dbf6325c23117665c3dd4abdb4aecc707bd28",
"index": 5,
"amount": 1,
"name": "Sigmanauts Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 6,
"amount": 500000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "3503ba6ce5d8bc1332229284c95fff15cf3c1d0b463fdfd6f3c9b57b7af09fe3",
"index": 7,
"amount": 1,
"name": "Good Things DAO Token",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "d31a913c625e83984201c26799f88ea09fe3e1b79f2e13536068a9baa956a348",
"index": 8,
"amount": 1,
"name": "Paideia Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3204f5cea36e3d3628cdc3708bfe55f23309fcfbe56c8d3a0e74a57b583dc921",
"index": 9,
"amount": 1,
"name": "Autolykos Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "e840e3bf0c4a3390d6ad9e3e9bcc14638e649feddcdd8d245f75b9738680fef6",
"index": 10,
"amount": 10,
"name": "LYKOS",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "8677bcc5692a427cd7c8443a1656836890ee55f3a3ce7405da785bc3ba6849ef",
"mainChain": true
}
],
"size": 5098,
"isUnconfirmed": false
}