Ad
Inputs (5)
Output transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.001 ERG
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
11.42 ERG
Tokens:
45,080.05
Outputs (7)
Spent in transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.1 ERG
Spent in transaction:
Settlement height:
Value:
0.00185 ERG
Spent in transaction:
Settlement height:
Value:
11.32 ERG
Tokens:
45,080.05
Transaction Details
Status: Confirmed
Size: 8.36 KB
Received time: 11/18/2024 01:55:30 PM
Included in blocks: 1,398,455
Confirmations: 360,094
Total coins transferred: 12.43 ERG
Fees: 0.00185 ERG
Fees per byte: 0.000000216 ERG
Raw Transaction Data
{
  "id": "0199ec3bf2db574021daa3c567019eebf5d89dee74493b358dac3c2252daff0b",
  "blockId": "b27fc9f48e10da80c62e3592082d19f76b950287fff9cb439b45f804bc294741",
  "inclusionHeight": 1398455,
  "timestamp": 1731938130844,
  "index": 3,
  "globalIndex": 8079075,
  "numConfirmations": 360094,
  "inputs": [
    {
      "boxId": "f5430fbbfcdbe87cee4a1aa51175c8bfb26fcb0b66b12b7a8e094b9442fac901",
      "value": 1000000000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "c6563c99ac042e243887870227398035d213c67144d1eed6e59912e5eb0f76e2",
      "outputTransactionId": "b47d125259dd53cb88fe778904bef5a2618d5437c426011fd0dbed99ec0a4d7d",
      "outputIndex": 0,
      "outputGlobalIndex": 43991205,
      "outputCreatedAt": 1398388,
      "outputSettledAt": 1398391,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)",
      "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": "233536261ad8920b85644d30fff8e68c470470138950317ad520b300e8c1e573",
          "index": 0,
          "amount": 1,
          "name": "Paideia Stake State",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
          "index": 1,
          "amount": 230018504024,
          "name": "Paideia",
          "decimals": 4,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "11078098a58eeb64aed5dee2b10d3400000000",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1732363200000,230018504023,26,0,0,0,0]"
        },
        "R6": {
          "serializedValue": "1d0501aed5dee2b10d012201f0bfa9c3f70b01140114",
          "sigmaType": "Coll[Coll[SLong]]",
          "renderedValue": "[[230018504023],[17],[205021065208],[10],[10]]"
        },
        "R8": {
          "serializedValue": "11020000",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[0,0]"
        },
        "R7": {
          "serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000a1d19c969232ef19b769772ed51c3a245e6ba22ee7461a6b74c2f76c31f9845d05072000",
          "sigmaType": null,
          "renderedValue": null
        },
        "R4": {
          "serializedValue": "0c6402b963da8c7d21a5956a3194981ca90e88c4275ca86935783645fdc673bc1ee206050720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
          "sigmaType": null,
          "renderedValue": null
        }
      }
    },
    {
      "boxId": "ea73eb089b14ecc3856f0c95655462b9c0b34bf1df37285e7f72fad47365f2c1",
      "value": 1000000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "8648afeb90e2fc2039342eaef83586fa0422a26a4d3603af6a04ef39c242331d",
      "outputTransactionId": "c55dc487b31a6a00e3ce3e78fe2482e0f0ca20e9898f2fc4d48ff0e8ce192349",
      "outputIndex": 1,
      "outputGlobalIndex": 43984636,
      "outputCreatedAt": 1398129,
      "outputSettledAt": 1398133,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n1: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
      "ergoTreeScript": "{\n  val coll1 = getVar[Coll[Coll[Byte]]](0.toByte).get\n  val coll2 = {(box2: Box) => box2.R4[AvlTree].get }(CONTEXT.dataInputs(0)).getMany(\n    Coll[Coll[Byte]](\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      ), Coll[Byte](\n        61.toByte, -86.toByte, 102.toByte, -128.toByte, -114.toByte, 105.toByte, -62.toByte, 90.toByte, -23.toByte, 50.toByte, -35.toByte, 102.toByte, 97.toByte, 28.toByte, 95.toByte, 11.toByte, 60.toByte, -70.toByte, -54.toByte, -47.toByte, 18.toByte, 82.toByte, 3.toByte, -24.toByte, 125.toByte, -115.toByte, -60.toByte, -111.toByte, -122.toByte, 28.toByte, 113.toByte, -26.toByte\n      )\n    ), coll1(0)\n  )\n  val coll3 = coll1(9)\n  val func4 = {(tuple4: (Coll[Box], Coll[Byte])) =>\n    tuple4._1.filter({(box6: Box) => box6.tokens.exists({(tuple8: (Coll[Byte], Long)) => tuple8._1 == tuple4._2 }) })\n  }\n  val coll5 = placeholder[Coll[Byte]](1)\n  val box6 = func4((OUTPUTS, coll5))(0)\n  val box7 = func4((INPUTS, coll5))(0)\n  val func8 = {(box8: Box) => box8.R4[Coll[AvlTree]].get(0) }\n  val avlTree9 = func8(box7)\n  val box10 = func4((INPUTS, {(opt10: Option[Coll[Byte]]) => opt10.get.slice(6, 38) }(coll2(1))))(0)\n  val coll11 = avlTree9.get(coll3, coll1(2)).get\n  val coll12 = longToByteArray(\n    max({(box12: Box) => box12.R5[Coll[Long]].get(0) }(box10), {(coll12: Coll[Byte]) => byteArrayToLong(coll12.slice(0, 8)) }(coll11))\n  ).append(coll11.slice(8, coll11.size))\n  val func13 = {(box13: Box) => box13.R4[Coll[AvlTree]].get(1) }\n  val avlTree14 = func13(box7)\n  val opt15 = avlTree14.get(coll3, coll1(4))\n  val bool16 = opt15.isDefined\n  val opt17 = {(box17: Box) => box17.R6[AvlTree].get }(box10).get(coll3, coll1(1))\n  val bool18 = opt17.isDefined\n  val l19 = if (bool16) { byteArrayToLong(opt15.get.slice(0, 8)) } else { 0L }\n  val l20 = if (bool18) { l19 } else { l19 + 1L }\n  val l21 = if (bool16) { byteArrayToLong(opt15.get.slice(8, 16)) } else { 0L }\n  val coll22 = coll1(8)\n  val l23 = coll22.indices.slice(0, coll22.size / 8).map({(i23: Int) => byteArrayToLong(coll22.slice(i23 * 8, i23 + 1 * 8)) }).fold(\n    0L, {(tuple23: (Long, Long)) => tuple23._1 + tuple23._2 }\n  )\n  val l24 = if (bool18) {(\n    val coll24 = opt17.get\n    max(\n      l21 - coll24.indices.slice(0, coll24.size / 8).map({(i25: Int) => byteArrayToLong(coll24.slice(i25 * 8, i25 + 1 * 8)) }).fold(\n        0L, {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }\n      ) + l23, 0L\n    )\n  )} else { l21 + l23 }\n  val coll25 = longToByteArray(l20).append(longToByteArray(l24))\n  val coll26 = coll1(5)\n  val func27 = {(box27: Box) => box27.R5[Coll[Long]].get(0) }\n  val func28 = {(box28: Box) => box28.R5[Coll[Long]].get(1) }\n  val func29 = {(box29: Box) => box29.R5[Coll[Long]].get(2) }\n  val func30 = {(box30: Box) => box30.R5[Coll[Long]].get(3) }\n  val func31 = {(box31: Box) => box31.R5[Coll[Long]].get(4) }\n  val func32 = {(box32: Box) =>\n    val coll34 = box32.R5[Coll[Long]].get\n    coll34.slice(5, coll34.size)\n  }\n  val func33 = {(box33: Box) => box33.R6[Coll[Coll[Long]]].get }\n  val func34 = {(box34: Box) => box34.R7[Coll[(AvlTree, AvlTree)]].get }\n  val func35 = {(box35: Box) => box35.R8[Coll[Long]].get }\n  sigmaProp(\n    allOf(\n      Coll[Boolean](\n        {(tuple36: (Coll[Box], Coll[Byte])) => tuple36._1.filter({(box38: Box) => blake2b256(box38.propositionBytes) == tuple36._2 }) }(\n          (OUTPUTS, {(opt36: Option[Coll[Byte]]) => opt36.get.slice(1, 33) }(coll2(0)))\n        )(0).value >= SELF.value, {(tuple36: (Coll[Box], Coll[Byte])) =>\n          tuple36._1.exists({(box38: Box) => box38.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == tuple36._2 }) })\n        }((OUTPUTS, coll3)), allOf(\n          Coll[Boolean](\n            box6.value == box7.value, box6.tokens == box7.tokens, func8(box6).digest == avlTree9.update(\n              Coll[(Coll[Byte], Coll[Byte])]((coll3, coll12)), coll1(3)\n            ).get.digest, func13(box6).digest == if (bool16) { avlTree14.update(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get } else {\n              avlTree14.insert(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get\n            }.digest, func27(box6) == func27(box7), func28(box6) == func28(box7), func29(box6) == func29(box7), func30(box6) == func30(\n              box7\n            ) + l20 - l19, func31(box6) == func31(box7) + l24 - l21, func32(box6) == func32(box7), func33(box6) == func33(box7), func34(box6) == func34(\n              box7\n            ), func35(box6) == func35(box7)\n          )\n        ), coll1(6) == coll12, coll1(7) == coll25\n      )\n    )\n  )\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {}
    },
    {
      "boxId": "63e224121f21830a573e820339f6d2fd5f6f1e5ceee3cceb50fa300b706b6b05",
      "value": 5000000,
      "index": 2,
      "spendingProof": null,
      "outputBlockId": "8648afeb90e2fc2039342eaef83586fa0422a26a4d3603af6a04ef39c242331d",
      "outputTransactionId": "c55dc487b31a6a00e3ce3e78fe2482e0f0ca20e9898f2fc4d48ff0e8ce192349",
      "outputIndex": 2,
      "outputGlobalIndex": 43984637,
      "outputCreatedAt": 1398129,
      "outputSettledAt": 1398133,
      "ergoTree": "10040e201b4b8b789fdd4a34c5f1cf73b4d99a5cacb8ccba75265f6edf4950893b162f070e201b4b8b789fdd4a34c5f1cf73b4d99a5cacb8ccba75265f6edf4950893b162f070e201fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad4890e20233536261ad8920b85644d30fff8e68c470470138950317ad520b300e8c1e573d815d601d9010163b2db63087201040000d602d901023c0c630eae8c720201d9010463aedb63087204d901064d0e938c7206018c720202d603db6503fed604e4e30002d605d9010563d801d607e4c672050511b472070404b17207d606e30a4005d607860204030500d6087207d609e572067208d60a8c720901d60b8c720902d60cd9010c3c0c630eb58c720c01d9010e6393cbc2720e8c720c02d60dd9010d63b2e4c6720d0410040000d60ed9010e63b2e4c6720e0511040200d60fd9010f63e4c6720f0664d610d9011063b2e4c672100410040200d6117303d612d901123c0c630eb58c721201d9011463aedb63087214d901164d0e938c7216018c721202d613d9011363e4c672130464d614d901143c324159d805d6168c721402d6178c721601d6188c721602d6198c721801d61a8c721802e5dc24078c72140101d9011b0e9593b1721b0412d801d61d7cb4721b04020412958f721d721772179591721d72197219721d721a721ad615d9011563b2e4c672150511040000d197830301dad901160295937216020cdad901181a968303019199db690572038cc7a70104e09e60af7218d9011a0eefda7202018602a5721a93b1a404020183010e8cda720101a7010100017204dad901160295937216020dd80fd618da720501a7d619c2a7d61ab2da720c018602a5cb7219040000d61bc1721ad61cda720e01a7d61ddb6501fed61e830002d61fdc640bda721301b2da7212018602721d73000400000283020e83200202f602ff028b0272021002010255024502d402b302ac025f02c6020c02900280029202d0023502a102a10261025502c0022902e802d502110262027c027a022c83200202af0278025b020a02dd0280025c025c023102f102cc023a023e029602c80290020802fd0271022702320201020702a30278024b027f024902e9025602480242e5e3010e721ed62086020502860205ce0f05e807d6217206d6227207d6237208d6247209d625dc640bda721301b2da7212018602721d73010400000283020e83200202f50291028e02b402b00228023c0266029b02dd028a0219025602400276026c021902e4020a0269023a0266029702b7027502b0028e020902050225022302d48320020276027c02aa028002b9028e0249026a02d802a902f6028902c40241020a02e402530232027f020f029502e90250028402c002ae0220026302500279023b0277e5e3020e721ed626b2da720c018602a5dad9012632b4e472260402044201b2722504020004000096830501ededafdb0c0e7218d901270495937227720a93b27218722700720b90b27218722700720b91b17218720a92720a04009683090193c2721a721992721b99c1a705809bee0292721b058092f40193da720101721ada720101a793da720d01721ada720d01a793da720e01721a721c93da720501721a721893da720f01721ada720f01a793da721001721a95ed92721c9d9cdad9012763b2e4c67227051104020001b2da7212018602721d7211040000da7214018602b2721f040000722005d00fd801d627720b9272279d9c721cda7214018602b2721f040200722005d00f720a040391db69037203da721501a79683020192c172260580897a92dad901273c0c630eb0dc0c0f8c72270101d9012963db630872290500d90129414d0ed801d62b8c7229029a8c72290195938c722b018c7227028c722b02050001860283016372267302a18cb2db6308a7040200027cb4e4b272250400000402041293da721001a704010100017204dad9011602959372160206d80ed618e4e3011ad619b27218040800d61ab27218040600d61badb4db0c0e721a04009db1721a0410d9011b047cb4721a9c721b04109c9a721b04020410d61cb0721b0500d9011c599a8c721c018c721c02d61dc2a7d61eb2da720c018602a5cb721d040000d61fda721501a7d620da720f01a7d621dc640a7220027219b27218040000d622e67221d623b27218040200d624da720501a7d625da720501721e96830c01927cb4e4dc640adad9012663b2e4c67226040c6404000001b2da7212018602a47211040000027219b2721804040004100420721c93c2721e721d92c1721ec1a793db6308721edb6308a793da720d01721eda720d01a793da721001721eda721001a793da721501721e721f93db6401da720f01721edb6401957222e4dc640d72200283013c0e0e86027219721a7223e4dc640c72200283013c0e0e86027219721a72238fdb69037203721f957222d802d626e47221d627adb4db0c0e722604009db172260410d90127047cb472269c722704109c9a7227040204109683020193da720e01721e9a99da720e01a7b072270500d90128599a8c7228018c722802721c937225addc0c1d722401addc0c1d722701721bd9012859998c7228028c722801d90128599a8c7228018c7228029683020193da720e01721e9ada720e01a7721c937225addc0c1d722401721bd90126599a8c7226018c722602da7202018602a4721994722572240100017204",
      "ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
      "ergoTreeScript": "{\n  val func1 = {(box1: Box) => box1.tokens(0) }\n  val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n    tuple2._1.exists({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n  }\n  val preHeader3 = CONTEXT.preHeader\n  val b4 = getVar[Byte](0.toByte).get\n  val func5 = {(box5: Box) =>\n    val coll7 = box5.R5[Coll[Long]].get\n    coll7.slice(2, coll7.size)\n  }\n  val opt6 = getVar[(Int, Long)](10.toByte)\n  val tuple7 = (-2, 0L)\n  val tuple8 = tuple7\n  val tuple9 = opt6.getOrElse(tuple8)\n  val i10 = tuple9._1\n  val l11 = tuple9._2\n  val func12 = {(tuple12: (Coll[Box], Coll[Byte])) => tuple12._1.filter({(box14: Box) => blake2b256(box14.propositionBytes) == tuple12._2 }) }\n  val func13 = {(box13: Box) => box13.R4[Coll[Int]].get(0) }\n  val func14 = {(box14: Box) => box14.R5[Coll[Long]].get(1) }\n  val func15 = {(box15: Box) => box15.R6[AvlTree].get }\n  val func16 = {(box16: Box) => box16.R4[Coll[Int]].get(1) }\n  val coll17 = placeholder[Coll[Byte]](3)\n  val func18 = {(tuple18: (Coll[Box], Coll[Byte])) =>\n    tuple18._1.filter({(box20: Box) => box20.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == tuple18._2 }) })\n  }\n  val func19 = {(box19: Box) => box19.R4[AvlTree].get }\n  val func20 = {(tuple20: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n    val tuple22 = tuple20._2\n    val l23 = tuple22._1\n    val tuple24 = tuple22._2\n    val l25 = tuple24._1\n    val l26 = tuple24._2\n    tuple20._1.map({(coll27: Coll[Byte]) => if (coll27.size == 9) {(\n          val l29 = byteArrayToLong(coll27.slice(1, 9))\n          if (l29 < l23) { l23 } else { if (l29 > l25) { l25 } else { l29 } }\n        )} else { l26 } }).getOrElse(l26)\n  }\n  val func21 = {(box21: Box) => box21.R5[Coll[Long]].get(0) }\n  sigmaProp(\n    anyOf(\n      Coll[Boolean](\n        {(b22: Byte) =>\n          if (b22 == 12.toByte) {\n            {(coll24: Coll[Coll[Byte]]) =>\n              allOf(\n                Coll[Boolean](\n                  preHeader3.height - SELF.creationInfo._1 > 788400, coll24.forall({(coll26: Coll[Byte]) => !func2((OUTPUTS, coll26)) }), INPUTS.size == 1\n                )\n              )\n            }(Coll[Coll[Byte]](func1(SELF)._1))\n          } else { false }\n        }(b4), {(b22: Byte) => if (b22 == 13.toByte) {(\n            val coll24 = func5(SELF)\n            val coll25 = SELF.propositionBytes\n            val box26 = func12((OUTPUTS, blake2b256(coll25)))(0)\n            val l27 = box26.value\n            val l28 = func14(SELF)\n            val coll29 = CONTEXT.dataInputs\n            val coll30 = Coll[Byte]()\n            val coll31 = func19(func18((coll29, placeholder[Coll[Byte]](0)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-10.toByte, -1.toByte, -117.toByte, 114.toByte, 16.toByte, 1.toByte, 85.toByte, 69.toByte, -44.toByte, -77.toByte, -84.toByte, 95.toByte, -58.toByte, 12.toByte, -112.toByte, -128.toByte, -110.toByte, -48.toByte, 53.toByte, -95.toByte, -95.toByte, 97.toByte, 85.toByte, -64.toByte, 41.toByte, -24.toByte, -43.toByte, 17.toByte, 98.toByte, 124.toByte, 122.toByte, 44.toByte), Coll[Byte](-81.toByte, 120.toByte, 91.toByte, 10.toByte, -35.toByte, -128.toByte, 92.toByte, 92.toByte, 49.toByte, -15.toByte, -52.toByte, 58.toByte, 62.toByte, -106.toByte, -56.toByte, -112.toByte, 8.toByte, -3.toByte, 113.toByte, 39.toByte, 50.toByte, 1.toByte, 7.toByte, -93.toByte, 120.toByte, 75.toByte, 127.toByte, 73.toByte, -23.toByte, 86.toByte, 72.toByte, 66.toByte)), getVar[Coll[Byte]](1.toByte).getOrElse(coll30))\n            val tuple32 = (1L, (999L, 500L))\n            val opt33 = opt6\n            val tuple34 = tuple7\n            val tuple35 = tuple8\n            val tuple36 = tuple9\n            val coll37 = func19(func18((coll29, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll30))\n            val box38 = func12((OUTPUTS, {(opt38: Option[Coll[Byte]]) => opt38.get.slice(1, 33) }(coll37(1))))(0)\n            allOf(Coll[Boolean]((coll24.indices.forall({(i39: Int) => if (i39 == i10) { coll24(i39) == l11 } else { coll24(i39) <= l11 } }) && (coll24.size > i10)) && (i10 >= 0), allOf(Coll[Boolean](box26.propositionBytes == coll25, l27 >= SELF.value - 3000000L, l27 >= 2000000L, func1(box26) == func1(SELF), func13(box26) == func13(SELF), func14(box26) == l28, func5(box26) == coll24, func15(box26) == func15(SELF), func16(box26) == if ((l28 >= {(box39: Box) => box39.R5[Coll[Long]].get(1) }(func18((coll29, coll17))(0)) * func20((coll31(0), tuple32)) / 1000L) && \n                      val l39 = l11\n                      l39 >= l28 * func20((coll31(1), tuple32)) / 1000L\n                    ) { i10 } else { -2 })), preHeader3.timestamp > func21(SELF), allOf(Coll[Boolean](box38.value >= 1000000L, {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.flatMap({(box41: Box) => box41.tokens }).fold(0L, {(tuple41: (Long, (Coll[Byte], Long))) =>\n                          val tuple43 = tuple41._2\n                          tuple41._1 + if (tuple43._1 == tuple39._2) { tuple43._2 } else { 0L }\n                        }) }((Coll[Box](box38), placeholder[Coll[Byte]](2))) >= min(SELF.tokens(1)._2, byteArrayToLong(coll37(0).get.slice(1, 9))))), func16(SELF) == -1))\n          )} else { false } }(b4), {(b22: Byte) => if (b22 == 6.toByte) {(\n            val coll24 = getVar[Coll[Coll[Byte]]](1.toByte).get\n            val coll25 = coll24(4)\n            val coll26 = coll24(3)\n            val coll27 = coll26.indices.slice(0, coll26.size / 8).map({(i27: Int) => byteArrayToLong(coll26.slice(i27 * 8, i27 + 1 * 8)) })\n            val l28 = coll27.fold(0L, {(tuple28: (Long, Long)) => tuple28._1 + tuple28._2 })\n            val coll29 = SELF.propositionBytes\n            val box30 = func12((OUTPUTS, blake2b256(coll29)))(0)\n            val l31 = func21(SELF)\n            val avlTree32 = func15(SELF)\n            val opt33 = avlTree32.get(coll25, coll24(0))\n            val bool34 = opt33.isDefined\n            val coll35 = coll24(1)\n            val coll36 = func5(SELF)\n            val coll37 = func5(box30)\n            allOf(Coll[Boolean](byteArrayToLong({(box38: Box) => box38.R4[Coll[AvlTree]].get(0) }(func18((INPUTS, coll17))(0)).get(coll25, coll24(2)).get.slice(8, 16)) >= l28, box30.propositionBytes == coll29, box30.value >= SELF.value, box30.tokens == SELF.tokens, func13(box30) == func13(SELF), func16(box30) == func16(SELF), func21(box30) == l31, func15(box30).digest == if (bool34) { avlTree32.update(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get } else { avlTree32.insert(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get }.digest, preHeader3.timestamp < l31, if (bool34) {(\n                  val coll38 = opt33.get\n                  val coll39 = coll38.indices.slice(0, coll38.size / 8).map({(i39: Int) => byteArrayToLong(coll38.slice(i39 * 8, i39 + 1 * 8)) })\n                  allOf(Coll[Boolean](func14(box30) == func14(SELF) - coll39.fold(0L, {(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 }) + l28, coll37 == coll36.zip(coll39.zip(coll27).map({(tuple40: (Long, Long)) => tuple40._2 - tuple40._1 })).map({(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 })))\n                )} else { allOf(Coll[Boolean](func14(box30) == func14(SELF) + l28, coll37 == coll36.zip(coll27).map({(tuple38: (Long, Long)) => tuple38._1 + tuple38._2 }))) }, func2((INPUTS, coll25)), coll37 != coll36))\n          )} else { false } }(b4)\n      )\n    )\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "0b2061b664725d7570fdfc40de19b554e60952ced7649f4ad4a9ee2c8640f7c3",
          "index": 0,
          "amount": 1,
          "name": "Paideia Proposal",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
          "index": 1,
          "amount": 10000000,
          "name": "Paideia",
          "decimals": 4,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "10020a01",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[5,-1]"
        },
        "R5": {
          "serializedValue": "1104c89d968fe864f0bfa9c3f70bc0d9e48e0bb0e6c4b4ec0b",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1731961472868,205021065208,1491900000,203529165208]"
        },
        "R6": {
          "serializedValue": "64c3e1bcb901f08f5b24082903564fe23aaaf8e45da7b0d8f7e10f5fb2266c29cc05072000",
          "sigmaType": null,
          "renderedValue": null
        },
        "R7": {
          "serializedValue": "0e175570646174652070726f66697420736861726520706374",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "5570646174652070726f66697420736861726520706374"
        }
      }
    },
    {
      "boxId": "98bb5d794084c1f7162698bbaaacdd0912af171554cdc1547d136a6dae03a3c6",
      "value": 1000000,
      "index": 3,
      "spendingProof": "91b1c7852331ab2c48b35bb63949ba1ba08232d6fc3c4f846764c67f2fbcffc71e49f10782fa89be26c94e0435d352e89ced7e147d7f043c",
      "outputBlockId": "bc871d09d6787f4e631ed78eb6b207d4658a05b2edcc27d568b1edd1bd39a97e",
      "outputTransactionId": "337c036925b09b302d8acad061d771fc904984d438e28f32bd8aed5ef6157c95",
      "outputIndex": 3,
      "outputGlobalIndex": 43723756,
      "outputCreatedAt": 1391337,
      "outputSettledAt": 1391339,
      "ergoTree": "0008cd0321d98546eb576ddcb29b31723f471e36ca6399667e48ec25903c9b718b79e9ec",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(21d985,1ad4ca,...)))}",
      "address": "9giiLTgUVktGDPhXJheMiEmvm6AuismsLk1rePJyUEwqaoNcZGk",
      "assets": [
        {
          "tokenId": "75e459b6b8d0d7e9c8a9b6b7ab29df2740a2ddc9932e5ea7c9cbd991f8ab994c",
          "index": 0,
          "amount": 1,
          "name": "Paideia Membership",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "9c0422defff4ac506c6c169fe269b08abe113ad1047a9b2cd22ffd56274ce6b4",
      "value": 11419830337,
      "index": 4,
      "spendingProof": "11faf6c6b14b49c195123b1ac86d277e03c3fb810b86bdab75d4f844b4b93691b7e55b5a2ddf5be061bd94178204c746f518773c3dbd907b",
      "outputBlockId": "bc871d09d6787f4e631ed78eb6b207d4658a05b2edcc27d568b1edd1bd39a97e",
      "outputTransactionId": "337c036925b09b302d8acad061d771fc904984d438e28f32bd8aed5ef6157c95",
      "outputIndex": 6,
      "outputGlobalIndex": 43723759,
      "outputCreatedAt": 1391337,
      "outputSettledAt": 1391339,
      "ergoTree": "0008cd0321d98546eb576ddcb29b31723f471e36ca6399667e48ec25903c9b718b79e9ec",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(21d985,1ad4ca,...)))}",
      "address": "9giiLTgUVktGDPhXJheMiEmvm6AuismsLk1rePJyUEwqaoNcZGk",
      "assets": [
        {
          "tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
          "index": 0,
          "amount": 1000,
          "name": "Paideia",
          "decimals": 4,
          "type": "EIP-004"
        },
        {
          "tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
          "index": 1,
          "amount": 450800458,
          "name": "bPaideia",
          "decimals": 4,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [
    {
      "boxId": "79c5d20aa64bf7608a714d516165bcb3991b4e55c9239407ca50e5ba8f6f2552",
      "value": 1000000000,
      "index": 0,
      "outputBlockId": "c86d5a5a0c51630cc9a369a60c05ad659e106e1b4ad240703468ff16ee597456",
      "outputTransactionId": "28a7d9c5ffb0350ac8dfa9d4d2b94d1b68836fd5896d04e3958db95802b5961d",
      "outputIndex": 0,
      "ergoTree": "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",
      "address": "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",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "64ed9d1be689a78f6a46a22fa3de3da4b5303e5189aece0f91ad8f5e384274c16a07072000",
          "sigmaType": null,
          "renderedValue": null
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "0f3383f02b2674ec79b01ae3c66a6eb9c2450e8338dea3c8950fc30efe4bc429",
      "transactionId": "0199ec3bf2db574021daa3c567019eebf5d89dee74493b358dac3c2252daff0b",
      "blockId": "b27fc9f48e10da80c62e3592082d19f76b950287fff9cb439b45f804bc294741",
      "value": 1000000000,
      "index": 0,
      "globalIndex": 43992443,
      "creationHeight": 1398453,
      "settlementHeight": 1398455,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)",
      "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": "233536261ad8920b85644d30fff8e68c470470138950317ad520b300e8c1e573",
          "index": 0,
          "amount": 1,
          "name": "Paideia Stake State",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
          "index": 1,
          "amount": 230018504024,
          "name": "Paideia",
          "decimals": 4,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "11078098a58eeb64aed5dee2b10d3402d698fefd040000",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1732363200000,230018504023,26,1,668976683,0,0]"
        },
        "R6": {
          "serializedValue": "1d0501aed5dee2b10d012201f0bfa9c3f70b01140114",
          "sigmaType": "Coll[Coll[SLong]]",
          "renderedValue": "[[230018504023],[17],[205021065208],[10],[10]]"
        },
        "R8": {
          "serializedValue": "11020000",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[0,0]"
        },
        "R7": {
          "serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000a1d19c969232ef19b769772ed51c3a245e6ba22ee7461a6b74c2f76c31f9845d05072000",
          "sigmaType": null,
          "renderedValue": null
        },
        "R4": {
          "serializedValue": "0c6402d1ee3f9dcec613d1ccd55baaf5e84976d5268ffba318500c0be82946755a8fc40507200097f30060a0aaa9224ffaff0a8880b85ba9787438081a48d3e8e4567c0bf603ca01072000",
          "sigmaType": null,
          "renderedValue": null
        }
      },
      "spentTransactionId": "ca6336965a9da9addfb2e512ac5bd388bfb5f813fda9c3c83ae56d8f13edafca",
      "mainChain": true
    },
    {
      "boxId": "4c111430bab161b40291f357061b81e8d9c82e258ac8db3f0ce952171021e3eb",
      "transactionId": "0199ec3bf2db574021daa3c567019eebf5d89dee74493b358dac3c2252daff0b",
      "blockId": "b27fc9f48e10da80c62e3592082d19f76b950287fff9cb439b45f804bc294741",
      "value": 1000000,
      "index": 1,
      "globalIndex": 43992444,
      "creationHeight": 1398453,
      "settlementHeight": 1398455,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n1: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
      "ergoTreeScript": "{\n  val coll1 = getVar[Coll[Coll[Byte]]](0.toByte).get\n  val coll2 = {(box2: Box) => box2.R4[AvlTree].get }(CONTEXT.dataInputs(0)).getMany(\n    Coll[Coll[Byte]](\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      ), Coll[Byte](\n        61.toByte, -86.toByte, 102.toByte, -128.toByte, -114.toByte, 105.toByte, -62.toByte, 90.toByte, -23.toByte, 50.toByte, -35.toByte, 102.toByte, 97.toByte, 28.toByte, 95.toByte, 11.toByte, 60.toByte, -70.toByte, -54.toByte, -47.toByte, 18.toByte, 82.toByte, 3.toByte, -24.toByte, 125.toByte, -115.toByte, -60.toByte, -111.toByte, -122.toByte, 28.toByte, 113.toByte, -26.toByte\n      )\n    ), coll1(0)\n  )\n  val coll3 = coll1(9)\n  val func4 = {(tuple4: (Coll[Box], Coll[Byte])) =>\n    tuple4._1.filter({(box6: Box) => box6.tokens.exists({(tuple8: (Coll[Byte], Long)) => tuple8._1 == tuple4._2 }) })\n  }\n  val coll5 = placeholder[Coll[Byte]](1)\n  val box6 = func4((OUTPUTS, coll5))(0)\n  val box7 = func4((INPUTS, coll5))(0)\n  val func8 = {(box8: Box) => box8.R4[Coll[AvlTree]].get(0) }\n  val avlTree9 = func8(box7)\n  val box10 = func4((INPUTS, {(opt10: Option[Coll[Byte]]) => opt10.get.slice(6, 38) }(coll2(1))))(0)\n  val coll11 = avlTree9.get(coll3, coll1(2)).get\n  val coll12 = longToByteArray(\n    max({(box12: Box) => box12.R5[Coll[Long]].get(0) }(box10), {(coll12: Coll[Byte]) => byteArrayToLong(coll12.slice(0, 8)) }(coll11))\n  ).append(coll11.slice(8, coll11.size))\n  val func13 = {(box13: Box) => box13.R4[Coll[AvlTree]].get(1) }\n  val avlTree14 = func13(box7)\n  val opt15 = avlTree14.get(coll3, coll1(4))\n  val bool16 = opt15.isDefined\n  val opt17 = {(box17: Box) => box17.R6[AvlTree].get }(box10).get(coll3, coll1(1))\n  val bool18 = opt17.isDefined\n  val l19 = if (bool16) { byteArrayToLong(opt15.get.slice(0, 8)) } else { 0L }\n  val l20 = if (bool18) { l19 } else { l19 + 1L }\n  val l21 = if (bool16) { byteArrayToLong(opt15.get.slice(8, 16)) } else { 0L }\n  val coll22 = coll1(8)\n  val l23 = coll22.indices.slice(0, coll22.size / 8).map({(i23: Int) => byteArrayToLong(coll22.slice(i23 * 8, i23 + 1 * 8)) }).fold(\n    0L, {(tuple23: (Long, Long)) => tuple23._1 + tuple23._2 }\n  )\n  val l24 = if (bool18) {(\n    val coll24 = opt17.get\n    max(\n      l21 - coll24.indices.slice(0, coll24.size / 8).map({(i25: Int) => byteArrayToLong(coll24.slice(i25 * 8, i25 + 1 * 8)) }).fold(\n        0L, {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }\n      ) + l23, 0L\n    )\n  )} else { l21 + l23 }\n  val coll25 = longToByteArray(l20).append(longToByteArray(l24))\n  val coll26 = coll1(5)\n  val func27 = {(box27: Box) => box27.R5[Coll[Long]].get(0) }\n  val func28 = {(box28: Box) => box28.R5[Coll[Long]].get(1) }\n  val func29 = {(box29: Box) => box29.R5[Coll[Long]].get(2) }\n  val func30 = {(box30: Box) => box30.R5[Coll[Long]].get(3) }\n  val func31 = {(box31: Box) => box31.R5[Coll[Long]].get(4) }\n  val func32 = {(box32: Box) =>\n    val coll34 = box32.R5[Coll[Long]].get\n    coll34.slice(5, coll34.size)\n  }\n  val func33 = {(box33: Box) => box33.R6[Coll[Coll[Long]]].get }\n  val func34 = {(box34: Box) => box34.R7[Coll[(AvlTree, AvlTree)]].get }\n  val func35 = {(box35: Box) => box35.R8[Coll[Long]].get }\n  sigmaProp(\n    allOf(\n      Coll[Boolean](\n        {(tuple36: (Coll[Box], Coll[Byte])) => tuple36._1.filter({(box38: Box) => blake2b256(box38.propositionBytes) == tuple36._2 }) }(\n          (OUTPUTS, {(opt36: Option[Coll[Byte]]) => opt36.get.slice(1, 33) }(coll2(0)))\n        )(0).value >= SELF.value, {(tuple36: (Coll[Box], Coll[Byte])) =>\n          tuple36._1.exists({(box38: Box) => box38.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == tuple36._2 }) })\n        }((OUTPUTS, coll3)), allOf(\n          Coll[Boolean](\n            box6.value == box7.value, box6.tokens == box7.tokens, func8(box6).digest == avlTree9.update(\n              Coll[(Coll[Byte], Coll[Byte])]((coll3, coll12)), coll1(3)\n            ).get.digest, func13(box6).digest == if (bool16) { avlTree14.update(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get } else {\n              avlTree14.insert(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get\n            }.digest, func27(box6) == func27(box7), func28(box6) == func28(box7), func29(box6) == func29(box7), func30(box6) == func30(\n              box7\n            ) + l20 - l19, func31(box6) == func31(box7) + l24 - l21, func32(box6) == func32(box7), func33(box6) == func33(box7), func34(box6) == func34(\n              box7\n            ), func35(box6) == func35(box7)\n          )\n        ), coll1(6) == coll12, coll1(7) == coll25\n      )\n    )\n  )\n}",
      "address": "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",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "0f7b90482b87bc9c58ae0cd561f299802f471aa28537c86493925b0ef429ca0d",
      "mainChain": true
    },
    {
      "boxId": "6f52e90bf0f30a7a70b6a863883b4757910a276ec2f23cce3e4ff8887c586c6f",
      "transactionId": "0199ec3bf2db574021daa3c567019eebf5d89dee74493b358dac3c2252daff0b",
      "blockId": "b27fc9f48e10da80c62e3592082d19f76b950287fff9cb439b45f804bc294741",
      "value": 5000000,
      "index": 2,
      "globalIndex": 43992445,
      "creationHeight": 1398453,
      "settlementHeight": 1398455,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
      "ergoTreeScript": "{\n  val func1 = {(box1: Box) => box1.tokens(0) }\n  val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n    tuple2._1.exists({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n  }\n  val preHeader3 = CONTEXT.preHeader\n  val b4 = getVar[Byte](0.toByte).get\n  val func5 = {(box5: Box) =>\n    val coll7 = box5.R5[Coll[Long]].get\n    coll7.slice(2, coll7.size)\n  }\n  val opt6 = getVar[(Int, Long)](10.toByte)\n  val tuple7 = (-2, 0L)\n  val tuple8 = tuple7\n  val tuple9 = opt6.getOrElse(tuple8)\n  val i10 = tuple9._1\n  val l11 = tuple9._2\n  val func12 = {(tuple12: (Coll[Box], Coll[Byte])) => tuple12._1.filter({(box14: Box) => blake2b256(box14.propositionBytes) == tuple12._2 }) }\n  val func13 = {(box13: Box) => box13.R4[Coll[Int]].get(0) }\n  val func14 = {(box14: Box) => box14.R5[Coll[Long]].get(1) }\n  val func15 = {(box15: Box) => box15.R6[AvlTree].get }\n  val func16 = {(box16: Box) => box16.R4[Coll[Int]].get(1) }\n  val coll17 = placeholder[Coll[Byte]](3)\n  val func18 = {(tuple18: (Coll[Box], Coll[Byte])) =>\n    tuple18._1.filter({(box20: Box) => box20.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == tuple18._2 }) })\n  }\n  val func19 = {(box19: Box) => box19.R4[AvlTree].get }\n  val func20 = {(tuple20: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n    val tuple22 = tuple20._2\n    val l23 = tuple22._1\n    val tuple24 = tuple22._2\n    val l25 = tuple24._1\n    val l26 = tuple24._2\n    tuple20._1.map({(coll27: Coll[Byte]) => if (coll27.size == 9) {(\n          val l29 = byteArrayToLong(coll27.slice(1, 9))\n          if (l29 < l23) { l23 } else { if (l29 > l25) { l25 } else { l29 } }\n        )} else { l26 } }).getOrElse(l26)\n  }\n  val func21 = {(box21: Box) => box21.R5[Coll[Long]].get(0) }\n  sigmaProp(\n    anyOf(\n      Coll[Boolean](\n        {(b22: Byte) =>\n          if (b22 == 12.toByte) {\n            {(coll24: Coll[Coll[Byte]]) =>\n              allOf(\n                Coll[Boolean](\n                  preHeader3.height - SELF.creationInfo._1 > 788400, coll24.forall({(coll26: Coll[Byte]) => !func2((OUTPUTS, coll26)) }), INPUTS.size == 1\n                )\n              )\n            }(Coll[Coll[Byte]](func1(SELF)._1))\n          } else { false }\n        }(b4), {(b22: Byte) => if (b22 == 13.toByte) {(\n            val coll24 = func5(SELF)\n            val coll25 = SELF.propositionBytes\n            val box26 = func12((OUTPUTS, blake2b256(coll25)))(0)\n            val l27 = box26.value\n            val l28 = func14(SELF)\n            val coll29 = CONTEXT.dataInputs\n            val coll30 = Coll[Byte]()\n            val coll31 = func19(func18((coll29, placeholder[Coll[Byte]](0)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-10.toByte, -1.toByte, -117.toByte, 114.toByte, 16.toByte, 1.toByte, 85.toByte, 69.toByte, -44.toByte, -77.toByte, -84.toByte, 95.toByte, -58.toByte, 12.toByte, -112.toByte, -128.toByte, -110.toByte, -48.toByte, 53.toByte, -95.toByte, -95.toByte, 97.toByte, 85.toByte, -64.toByte, 41.toByte, -24.toByte, -43.toByte, 17.toByte, 98.toByte, 124.toByte, 122.toByte, 44.toByte), Coll[Byte](-81.toByte, 120.toByte, 91.toByte, 10.toByte, -35.toByte, -128.toByte, 92.toByte, 92.toByte, 49.toByte, -15.toByte, -52.toByte, 58.toByte, 62.toByte, -106.toByte, -56.toByte, -112.toByte, 8.toByte, -3.toByte, 113.toByte, 39.toByte, 50.toByte, 1.toByte, 7.toByte, -93.toByte, 120.toByte, 75.toByte, 127.toByte, 73.toByte, -23.toByte, 86.toByte, 72.toByte, 66.toByte)), getVar[Coll[Byte]](1.toByte).getOrElse(coll30))\n            val tuple32 = (1L, (999L, 500L))\n            val opt33 = opt6\n            val tuple34 = tuple7\n            val tuple35 = tuple8\n            val tuple36 = tuple9\n            val coll37 = func19(func18((coll29, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll30))\n            val box38 = func12((OUTPUTS, {(opt38: Option[Coll[Byte]]) => opt38.get.slice(1, 33) }(coll37(1))))(0)\n            allOf(Coll[Boolean]((coll24.indices.forall({(i39: Int) => if (i39 == i10) { coll24(i39) == l11 } else { coll24(i39) <= l11 } }) && (coll24.size > i10)) && (i10 >= 0), allOf(Coll[Boolean](box26.propositionBytes == coll25, l27 >= SELF.value - 3000000L, l27 >= 2000000L, func1(box26) == func1(SELF), func13(box26) == func13(SELF), func14(box26) == l28, func5(box26) == coll24, func15(box26) == func15(SELF), func16(box26) == if ((l28 >= {(box39: Box) => box39.R5[Coll[Long]].get(1) }(func18((coll29, coll17))(0)) * func20((coll31(0), tuple32)) / 1000L) && \n                      val l39 = l11\n                      l39 >= l28 * func20((coll31(1), tuple32)) / 1000L\n                    ) { i10 } else { -2 })), preHeader3.timestamp > func21(SELF), allOf(Coll[Boolean](box38.value >= 1000000L, {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.flatMap({(box41: Box) => box41.tokens }).fold(0L, {(tuple41: (Long, (Coll[Byte], Long))) =>\n                          val tuple43 = tuple41._2\n                          tuple41._1 + if (tuple43._1 == tuple39._2) { tuple43._2 } else { 0L }\n                        }) }((Coll[Box](box38), placeholder[Coll[Byte]](2))) >= min(SELF.tokens(1)._2, byteArrayToLong(coll37(0).get.slice(1, 9))))), func16(SELF) == -1))\n          )} else { false } }(b4), {(b22: Byte) => if (b22 == 6.toByte) {(\n            val coll24 = getVar[Coll[Coll[Byte]]](1.toByte).get\n            val coll25 = coll24(4)\n            val coll26 = coll24(3)\n            val coll27 = coll26.indices.slice(0, coll26.size / 8).map({(i27: Int) => byteArrayToLong(coll26.slice(i27 * 8, i27 + 1 * 8)) })\n            val l28 = coll27.fold(0L, {(tuple28: (Long, Long)) => tuple28._1 + tuple28._2 })\n            val coll29 = SELF.propositionBytes\n            val box30 = func12((OUTPUTS, blake2b256(coll29)))(0)\n            val l31 = func21(SELF)\n            val avlTree32 = func15(SELF)\n            val opt33 = avlTree32.get(coll25, coll24(0))\n            val bool34 = opt33.isDefined\n            val coll35 = coll24(1)\n            val coll36 = func5(SELF)\n            val coll37 = func5(box30)\n            allOf(Coll[Boolean](byteArrayToLong({(box38: Box) => box38.R4[Coll[AvlTree]].get(0) }(func18((INPUTS, coll17))(0)).get(coll25, coll24(2)).get.slice(8, 16)) >= l28, box30.propositionBytes == coll29, box30.value >= SELF.value, box30.tokens == SELF.tokens, func13(box30) == func13(SELF), func16(box30) == func16(SELF), func21(box30) == l31, func15(box30).digest == if (bool34) { avlTree32.update(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get } else { avlTree32.insert(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get }.digest, preHeader3.timestamp < l31, if (bool34) {(\n                  val coll38 = opt33.get\n                  val coll39 = coll38.indices.slice(0, coll38.size / 8).map({(i39: Int) => byteArrayToLong(coll38.slice(i39 * 8, i39 + 1 * 8)) })\n                  allOf(Coll[Boolean](func14(box30) == func14(SELF) - coll39.fold(0L, {(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 }) + l28, coll37 == coll36.zip(coll39.zip(coll27).map({(tuple40: (Long, Long)) => tuple40._2 - tuple40._1 })).map({(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 })))\n                )} else { allOf(Coll[Boolean](func14(box30) == func14(SELF) + l28, coll37 == coll36.zip(coll27).map({(tuple38: (Long, Long)) => tuple38._1 + tuple38._2 }))) }, func2((INPUTS, coll25)), coll37 != coll36))\n          )} else { false } }(b4)\n      )\n    )\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "0b2061b664725d7570fdfc40de19b554e60952ced7649f4ad4a9ee2c8640f7c3",
          "index": 0,
          "amount": 1,
          "name": "Paideia Proposal",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
          "index": 1,
          "amount": 10000000,
          "name": "Paideia",
          "decimals": 4,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "10020a01",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[5,-1]"
        },
        "R5": {
          "serializedValue": "1104c89d968fe864c6d8a7c1fc0bc0d9e48e0b86ffc2b2f10b",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1731961472868,205690041891,1491900000,204198141891]"
        },
        "R6": {
          "serializedValue": "646404caa6d7282915f37dd8ced9218015f304daa319f194fcd11b9eaaa4cb93a705072000",
          "sigmaType": null,
          "renderedValue": null
        },
        "R7": {
          "serializedValue": "0e175570646174652070726f66697420736861726520706374",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "5570646174652070726f66697420736861726520706374"
        }
      },
      "spentTransactionId": "0f7b90482b87bc9c58ae0cd561f299802f471aa28537c86493925b0ef429ca0d",
      "mainChain": true
    },
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}