Transaction
ID: 862b95fba5...f777
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:
5.57 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...
Unspent
Address:
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:
0.2 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00185 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
5.36 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 293,695
Total coins transferred: 6.57 ERG
Fees: 0.00185 ERG
Fees per byte: 0.000000158 ERG
Raw Transaction Data
{
"id": "862b95fba5a1b512eeeacc3ce3c8fe1750d6571074577c19153e61a36fbff777",
"blockId": "c5b4359b6aab9d1905cc5a6304750d65efdcc32ea375737e6269fdb152545e5f",
"inclusionHeight": 1469411,
"timestamp": 1740523930022,
"index": 12,
"globalIndex": 8636603,
"numConfirmations": 293695,
"inputs": [
{
"boxId": "f433f69c226e5c5eca06a02636a66152727d8a8438271ba7b987fbf5c5d4197a",
"value": 1000000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "74f1252e9d79b7c38eff42aa24a4859e3c983574129e93780db201b306bf67c0",
"outputTransactionId": "163d02db72087cd2e838d9a2bb6660cb5c4d7a51eafc8a321691fab27b8f90f4",
"outputIndex": 0,
"outputGlobalIndex": 46478439,
"outputCreatedAt": 1468776,
"outputSettledAt": 1468779,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\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(-101,126,-88,-71,-85,-85,125,46,96,-91,-39,44,107,25,57,-81,26,124,19,-104,90,-108,46,-19,-108,-29,-36,90,-81,55,-68,-125)",
"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": "38e5ce513bf85098e8f476a24287fccbf273c9f19d522ee07990e2df721e3bbc",
"index": 1,
"amount": 9223372036854776000,
"name": "Sigmanauts Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f86dd8f0a39ba59032865b2843401d4601d01a6e778c4afcad879328cfb3139c",
"index": 2,
"amount": 9223372036854776000,
"name": "Sigmanauts Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "0f7ab1aaa55b667024fc2575cfd2b7725fd70012ddd8967b3a46a08d515573cb",
"value": 1000000,
"index": 1,
"spendingProof": "84c7d9b7eea2a0ec4977e1214b80a4faa70b0b61403700eb6e59d50e779881378b7f9a21405aadb28136cef8ab92c3541d5561a7abd7af70",
"outputBlockId": "352faca694ebab7f1f4963fd32e2f6b3b1076066153ed3c03ae2fb86e8d4a3d4",
"outputTransactionId": "e9544c1de073dfa4f6de3a58797cd1e83b1db246150af38dfedb3babf783669d",
"outputIndex": 3,
"outputGlobalIndex": 46499855,
"outputCreatedAt": 1469303,
"outputSettledAt": 1469305,
"ergoTree": "0008cd028c945947b43157d9006ba85e05cddea5b527a9af821eacb2eb9e8fc55af6fd36",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8c9459,aa05aa,...)))}",
"address": "9fayRrb8wGmJcCHMg1phwzCTaLf3sZAX7BiJrQhPFUAshceX71u",
"assets": [
{
"tokenId": "d577aa18ae22a1667f5509796de26b64bc4964407db10e80ee2d1b05f2bdf091",
"index": 0,
"amount": 1,
"name": "Sigmanauts Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "cc3b5efca9f61ef2cb5356ebc015c22ee4582c65ad15ce2229af6e5efebf1f17",
"value": 5573559814,
"index": 2,
"spendingProof": "36a88af4f5b1752026f908b9e2dc3faa18f6dc8af18a4cb3ded630ee7bddfafe1cbc1da99280c98953d5f93c3b7daf0b6ce7258922e2e2cb",
"outputBlockId": "352faca694ebab7f1f4963fd32e2f6b3b1076066153ed3c03ae2fb86e8d4a3d4",
"outputTransactionId": "e9544c1de073dfa4f6de3a58797cd1e83b1db246150af38dfedb3babf783669d",
"outputIndex": 6,
"outputGlobalIndex": 46499858,
"outputCreatedAt": 1469303,
"outputSettledAt": 1469305,
"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": 5000000,
"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": "87095cd8640c37893e25dbe4f67dbd8b2564298b7666ec44b0f207d855448b6a",
"index": 8,
"amount": 1,
"name": "Walrus DAO 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": "53f02a91a6e79264a048e79ef506de8fdd48c86790b900c05c5893a6fe10d96b",
"value": 1000000000,
"index": 1,
"outputBlockId": "23c94deb8121036a5b3918c92061b1ce22f50cfe9eddae36e59c192166d72123",
"outputTransactionId": "6a0107ac5dfabf21418217f5f73dd2e1afbc586d66a76f751526c86e2ee020cc",
"outputIndex": 0,
"ergoTree": "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",
"address": "GcZsF9LKJimnp2rmnnexwvaXJ2LQPj7mN8eaoM47frYcziKfR1N8dc1fRWWYn8VePdW7J3wp2knYLa3tZCxxuQuGp99ndjDfxRpoKeJ1CEvVR1m7Pb47CNwijmCXewjgocGuZqm34NMbty4WbjXYxaZunEbgmVCratkNfne7ghnuHbB67FewT3K5DUrBiCTuw28auz8kS6TxpuvSQeyPJdFPm5ZMRDU2fanF1snGe2GizKBFh35czyjvC7oJ9Q5qUBHKXRgfZtgtZFmdysCqZ6r9HVdXvr1xEV2YmY5oJ8aS34dfCJxuzxYLaNqiMV8kUZfLR3HRqvv3EArTezUxDNf2qqez1iJs4pNY4Jx9mmWVn3NiCxUBaP44A5akyvhab4Fpb7v8FgEtrTHq4ki9nKawRNJ3GGGSX17VNZ4cYsrdqXsVqH4M1Jf2YpE13DyMPVXp4qm6HwED1Q1M1KS97zfjp4Q9D2sbGEE73AqusYQx1bD9LCFnHTrk93uTkBYK21iNX9v95PU7oHqzNbYVZgfnGYRHkXEAbMfXKaKidH87gc1Mgu9VpyDJgrFExmZ4vZgLzFwBChgmW5prZyqrop4RT7vgde55GyaQu8NWb5TB7UTXKbugpnfcAsg8R4dwqt8yA9oSQqADCTwtDtLumXiaKPmB9iHNBjZGQ2JNBX33hBya6xi79ziXEZ5Ph7rXzmvDC94yNwRzHL639B5CrXD4XAyBqgnDXvNhYR4p9gznJFKnC2BZbU7JEyEezaRsPZFVWbhH2sKpHo1S9WqyipXarb92hAfqiecwwNp2BrmUATJneqXa9BE4ieqLtsmREVFXMszrTfYaawTeMjrrnhbZKKRq77YA7H5rcoj6zPCib1oSHCMVwQxJdT6sABWjtQmg8u6ih7r4fgFhvzUxGvcct1dkbCBBaL85nER4gqaGeeBSo9U",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64c3304886c37ddc9c10620d2260693c33ba9a16a33cc50d80709639b115a4643206072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "ff8f2fd36d0f0a0b6ed4181f1790582de783b39ce2678b86cb46cf0f5acaa78a",
"value": 1000000000,
"index": 2,
"outputBlockId": "ba4d60a79a7d901b596d79a67013b0e5d4676da56eb1bd72f5dffe2f175753c8",
"outputTransactionId": "31d9f7edf4094f9bf6a8c2628c3a9f61ac347c3922dfc375a77d7de08ca0746e",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "1107d08fa2acba65201e16160000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1742997832680,16,15,11,11,0,0]"
},
"R6": {
"serializedValue": "1d0501200100010001320132",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[16],[0],[0],[25],[25]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c6402a21b8966d2b928c7c97c16100e1076a898bf7af0743c2c100ca4ee85cbe4606105072000d1821589f38fee40be9e2066e71d1ab09030b64b7bf9eb7e82400eb100af848d03072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "e1a713124325f6775f4e0ee1945139df87d0a16889b18939c42dd4ae498195a3",
"transactionId": "862b95fba5a1b512eeeacc3ce3c8fe1750d6571074577c19153e61a36fbff777",
"blockId": "c5b4359b6aab9d1905cc5a6304750d65efdcc32ea375737e6269fdb152545e5f",
"value": 1000000000,
"index": 0,
"globalIndex": 46504434,
"creationHeight": 1469409,
"settlementHeight": 1469411,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\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(-101,126,-88,-71,-85,-85,125,46,96,-91,-39,44,107,25,57,-81,26,124,19,-104,90,-108,46,-19,-108,-29,-36,90,-81,55,-68,-125)",
"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": "38e5ce513bf85098e8f476a24287fccbf273c9f19d522ee07990e2df721e3bbc",
"index": 1,
"amount": 9223372036854776000,
"name": "Sigmanauts Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f86dd8f0a39ba59032865b2843401d4601d01a6e778c4afcad879328cfb3139c",
"index": 2,
"amount": 9223372036854776000,
"name": "Sigmanauts Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d98741b8300e0455d90ed46cd4b274ff2e9700a44e294bca85a684d55f2cad6d",
"mainChain": true
},
{
"boxId": "362a0295f172ed5bad3beec148afb6326cc3fc400aa2fdd3b590ec69eb16dc22",
"transactionId": "862b95fba5a1b512eeeacc3ce3c8fe1750d6571074577c19153e61a36fbff777",
"blockId": "c5b4359b6aab9d1905cc5a6304750d65efdcc32ea375737e6269fdb152545e5f",
"value": 5000000,
"index": 1,
"globalIndex": 46504435,
"creationHeight": 1469409,
"settlementHeight": 1469411,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\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(-101,126,-88,-71,-85,-85,125,46,96,-91,-39,44,107,25,57,-81,26,124,19,-104,90,-108,46,-19,-108,-29,-36,90,-81,55,-68,-125)",
"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": "38e5ce513bf85098e8f476a24287fccbf273c9f19d522ee07990e2df721e3bbc",
"index": 0,
"amount": 1,
"name": "Sigmanauts Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 1,
"amount": 5000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "10021a01",
"sigmaType": "Coll[SInt]",
"renderedValue": "[13,-1]"
},
"R5": {
"serializedValue": "1104dafdc3b6ac65000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1741129547629,0,0,0]"
},
"R6": {
"serializedValue": "644ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R7": {
"serializedValue": "0e255550444154452053706f6e736f72204359505820486170707920486f7572205072697a6573",
"sigmaType": "Coll[SByte]",
"renderedValue": "5550444154452053706f6e736f72204359505820486170707920486f7572205072697a6573"
}
},
"spentTransactionId": "4d687d9e7c59d9de9b83fdf4810aa2fffa979e9f465b5085cee142cf930174e5",
"mainChain": true
},
{
"boxId": "550c04667ff06546308b3798d910340d00b530ac29c7855433a0165f9b0b9816",
"transactionId": "862b95fba5a1b512eeeacc3ce3c8fe1750d6571074577c19153e61a36fbff777",
"blockId": "c5b4359b6aab9d1905cc5a6304750d65efdcc32ea375737e6269fdb152545e5f",
"value": 2000000,
"index": 2,
"globalIndex": 46504436,
"creationHeight": 1469409,
"settlementHeight": 1469411,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\n1: Coll(56,-27,-50,81,59,-8,80,-104,-24,-12,118,-94,66,-121,-4,-53,-14,115,-55,-15,-99,82,46,-32,121,-112,-30,-33,114,30,59,-68)",
"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 coll4 = placeholder[Coll[Byte]](1)\n val func5 = {(tuple5: (Coll[Box], Coll[Byte])) =>\n tuple5._1.filter({(box7: Box) => box7.tokens.exists({(tuple9: (Coll[Byte], Long)) => tuple9._1 == tuple5._2 }) })\n }\n val func6 = {(box6: Box) => box6.R4[Coll[Long]].get(0) }\n val func7 = {(box7: Box) => box7.R4[Coll[Long]].get(1) }\n val func8 = {(box8: Box) => box8.R4[Coll[Long]].get(3) }\n val func9 = {(box9: Box) => box9.R4[Coll[Long]].get(2) }\n val func10 = {(box10: Box) => box10.R5[Coll[Box]].get }\n val func11 = {(box11: Box) => box11.R4[Coll[Long]].get(4) }\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 val func13 = {(box13: Box) =>\n val coll15 = box13.bytesWithoutRef\n val i16 = func12(box13.value) + box13.propositionBytes.size\n coll15.slice(0, i16).append(coll15.slice(i16 + func12(box13.creationInfo._1.toLong), coll15.size))\n }\n val func14 = {(coll14: Coll[Box]) =>\n coll14.flatMap({(box16: Box) => box16.tokens }).fold(0L, {(tuple16: (Long, (Coll[Byte], Long))) => tuple16._1 + tuple16._2._2 })\n }\n if (getVar[Byte](0.toByte).get == 12.toByte) {\n sigmaProp(\n {(coll15: Coll[Coll[Byte]]) =>\n allOf(\n Coll[Boolean](\n preHeader3.height - SELF.creationInfo._1 > 788400, coll15.forall({(coll17: Coll[Byte]) => !func2((OUTPUTS, coll17)) }), INPUTS.size == 1\n )\n )\n }(Coll[Coll[Byte]](func1(SELF)._1))\n )\n } else {(\n val coll15 = CONTEXT.dataInputs\n val box16 = func5((coll15, coll4))(0)\n val l17 = func9(SELF)\n val bool18 = l17 > 0L\n val coll19 = func10(SELF)\n val i20 = coll19.size\n val i21 = OUTPUTS.size\n val box22 = OUTPUTS(i21 - 1)\n val bool23 = blake2b256(box22.propositionBytes) == {(opt23: Option[Coll[Byte]]) => opt23.get.slice(1, 33) }(\n {(box23: Box) => box23.R4[AvlTree].get }(func5((coll15, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n -57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte\n )\n ), getVar[Coll[Byte]](1.toByte).get\n )(0)\n )\n val box24 = if (bool23) { OUTPUTS(i21 - 2) } else { box22 }\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n {(box25: Box) => box25.tokens(0) }(box16)._1 == coll4, {(box25: Box) => box25.R4[Coll[Int]].get(0) }(box16).toLong == func6(SELF), {(\n box25: Box\n ) => box25.R4[Coll[Int]].get(1) }(box16).toLong == func7(SELF)\n )\n ), preHeader3.timestamp >= func8(SELF), if (bool18) {(\n val coll25 = func10(SELF)\n val box26 = OUTPUTS(coll25.size)\n val l27 = func11(SELF)\n allOf(\n Coll[Boolean](\n box26.value == SELF.value, box26.tokens == SELF.tokens, func6(box26) == func6(SELF), func7(box26) == func7(SELF), func9(\n box26\n ) == l17 - 1L, func8(box26) == func8(SELF) + l27, func11(box26) == l27, func10(box26) == coll25, box26.propositionBytes == SELF.propositionBytes\n )\n )\n )} else { !func2((OUTPUTS, func1(SELF)._1)) }, coll19.zip(OUTPUTS.slice(0, i20)).forall(\n {(tuple25: (Box, Box)) => func13(tuple25._1) == func13(tuple25._2) }\n ), i21 == i20 + if (bool18) { 1 } else { 0 } + if (bool23) { 2 } else { 1 }, func14(INPUTS) == func14(OUTPUTS) + if (bool18) { 0L } else {\n 1L\n }, allOf(Coll[Boolean](box24.value <= 5000000L, box24.tokens.size == 0))\n )\n )\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "f86dd8f0a39ba59032865b2843401d4601d01a6e778c4afcad879328cfb3139c",
"index": 0,
"amount": 1,
"name": "Sigmanauts Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "11051a0200c0e4f1b8ac6500",
"sigmaType": "Coll[SLong]",
"renderedValue": "[13,1,0,1741132020000,0]"
},
"R5": {
"serializedValue": "0c6302c0b19f050008cd028c945947b43157d9006ba85e05cddea5b527a9af821eacb2eb9e8fc55af6fd36e1d7590169a1c6f11d2fd52e8914e17608a5e4b4e94842bfb670ab4aaaa9502e9a96befc3200f7289b9f55edee6552bcdb09faf1e035950ab4fb5f73faa294bcc3dd3cc0d9b300c0b19f050008cd0342cc3eae917d6e6eed082d47de583de67fc72d23640e95983e85f0588a71cc1ce1d7590169a1c6f11d2fd52e8914e17608a5e4b4e94842bfb670ab4aaaa9502e9a96befc01007708e2377934851815ef2bdd7604965056d6cc83d754522df0cfb9dc86104b6900",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "c0030e6b9f052977e9c7497bf299caa7b16e13a01835b1f62462e919f01ac082",
"transactionId": "862b95fba5a1b512eeeacc3ce3c8fe1750d6571074577c19153e61a36fbff777",
"blockId": "c5b4359b6aab9d1905cc5a6304750d65efdcc32ea375737e6269fdb152545e5f",
"value": 1000000,
"index": 3,
"globalIndex": 46504437,
"creationHeight": 1469409,
"settlementHeight": 1469411,
"ergoTree": "0008cd028c945947b43157d9006ba85e05cddea5b527a9af821eacb2eb9e8fc55af6fd36",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(8c9459,aa05aa,...)))}",
"address": "9fayRrb8wGmJcCHMg1phwzCTaLf3sZAX7BiJrQhPFUAshceX71u",
"assets": [
{
"tokenId": "d577aa18ae22a1667f5509796de26b64bc4964407db10e80ee2d1b05f2bdf091",
"index": 0,
"amount": 1,
"name": "Sigmanauts Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "215cb141afdecb7e66b7df13f6202d3a9d3b85550c90f22c0016ea6cda2c8778",
"mainChain": true
},
{
"boxId": "e5705bcdf8a2a3f8947bf1663e971d4d30118c29920d07a25ae7b6a5397511fe",
"transactionId": "862b95fba5a1b512eeeacc3ce3c8fe1750d6571074577c19153e61a36fbff777",
"blockId": "c5b4359b6aab9d1905cc5a6304750d65efdcc32ea375737e6269fdb152545e5f",
"value": 200000000,
"index": 4,
"globalIndex": 46504438,
"creationHeight": 1469409,
"settlementHeight": 1469411,
"ergoTree": "0008cd03553448c194fdd843c87d080f5e8ed983f5bb2807b13b45a9683bba8c7bfb5ae8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(553448,8bebb3,...)))}",
"address": "9h7L7sUHZk43VQC3PHtSp5ujAWcZtYmWATBH746wi75C5XHi68b",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "a04278b38f04dc9b4fe73a68c4eb170a7f0ab34c04b11ca8054c231060fc4b38",
"mainChain": true
},
{
"boxId": "6edf7211d7f396843668b4c7f3435a8e9baef244b2eb92ddb4f8ce1bd1e8875f",
"transactionId": "862b95fba5a1b512eeeacc3ce3c8fe1750d6571074577c19153e61a36fbff777",
"blockId": "c5b4359b6aab9d1905cc5a6304750d65efdcc32ea375737e6269fdb152545e5f",
"value": 1850000,
"index": 5,
"globalIndex": 46504439,
"creationHeight": 1469409,
"settlementHeight": 1469411,
"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": "2e123a94ccc649cedec289a7c98bb5eb3ff28d019222789e57c784637d62ab5b",
"mainChain": true
},
{
"boxId": "172c9472b9caa9c419b32095bae5294402075c87f920c0667fcb8c7c912f6f4e",
"transactionId": "862b95fba5a1b512eeeacc3ce3c8fe1750d6571074577c19153e61a36fbff777",
"blockId": "c5b4359b6aab9d1905cc5a6304750d65efdcc32ea375737e6269fdb152545e5f",
"value": 5364709814,
"index": 6,
"globalIndex": 46504440,
"creationHeight": 1469409,
"settlementHeight": 1469411,
"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": "a650291cd343d511a435b8720476736fcaf3e6c87f977b4e8123bcff666543be",
"index": 5,
"amount": 35,
"name": "Ergo DevDAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3503ba6ce5d8bc1332229284c95fff15cf3c1d0b463fdfd6f3c9b57b7af09fe3",
"index": 6,
"amount": 1,
"name": "Good Things DAO Token",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "87095cd8640c37893e25dbe4f67dbd8b2564298b7666ec44b0f207d855448b6a",
"index": 7,
"amount": 1,
"name": "Walrus DAO Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "95fe46189bebf31393adbb70ed5ee10412d68b49b34d8ff410c836137e3b6c31",
"mainChain": true
}
],
"size": 11702,
"isUnconfirmed": false
}