Ad
Inputs (2)
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
2,355.91 ERG
Tokens:
Loading assets...
Outputs (3)
Spent in transaction:
Settlement height:
Value:
500 ERG
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent in transaction:
Settlement height:
Value:
1,855.91 ERG
Tokens:
Loading assets...
Transaction Details
Status: Confirmed
Size: 3.35 KB
Received time: 7/6/2025 08:33:11 PM
Included in blocks: 1,562,861
Confirmations: 205,210
Total coins transferred: 2,355.91 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000291 ERG
Raw Transaction Data
{
  "id": "ad85c7d9a0b012095b3d6c1e7d3eb7d95caf6836cf944791f63fcf4f76c508af",
  "blockId": "4ad5cca07a183dd6453cf431076b40b86acba873c920f8cf7408358e84d4ec25",
  "inclusionHeight": 1562861,
  "timestamp": 1751833991647,
  "index": 2,
  "globalIndex": 9176756,
  "numConfirmations": 205210,
  "inputs": [
    {
      "boxId": "f54ca09c867926d63367d34ff93747f76111caccf6f9bf933660df8191f3792c",
      "value": 2000000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "cad04ff175e49276fb7cc9896f1dc4335fd05b2bdaeca64662ca7013b4b293c9",
      "outputTransactionId": "c9644ff37d61a6ed64ef2675a024554fbf5d75c196213847f3372e26bc9ab993",
      "outputIndex": 2,
      "outputGlobalIndex": 48665832,
      "outputCreatedAt": 1559312,
      "outputSettledAt": 1559313,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(126,-119,-126,-122,21,45,53,37,-18,-76,-34,-118,29,-125,58,61,92,-95,-6,120,-71,10,-24,61,-102,15,4,-63,66,31,66,-68)\n1: Coll(126,-96,-83,46,29,67,107,-62,-64,-5,100,86,-11,105,-16,120,42,22,54,27,97,-58,102,-118,-8,12,46,24,-72,85,-40,-45)",
      "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": "6ca1155beb332c95d6d542508b5fd5d538078cf031cd8f7c716bf18ad9c0d8d2",
          "index": 0,
          "amount": 1,
          "name": "DevDAO Action",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1105060200c0ce8ba7fa6500",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[3,1,0,1751582340000,0]"
        },
        "R5": {
          "serializedValue": "0c6301c09487d3c60e0008cd0216133993bbc54c0d48a21634a7d2632b8c92d744d565839dc39c912ef406e0d990965f00000f557efc3e1df49e8bf18218a20e4f0b779fa8ae2ee40e55b39e357c839d8db100",
          "sigmaType": null,
          "renderedValue": null
        }
      }
    },
    {
      "boxId": "5703450cc2446f310fa2e74b7cdf14d8acfb215bad068e8bb6495be8d142f6c4",
      "value": 2355907000000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "91db0400afb7ab5ba1729facc8e13a17a9aa2d263697b34f4a6d83c0685174fe",
      "outputTransactionId": "0aefadabd0256aa9afc1ed7856384fc73714bd0ffa43944234f27c67baae499d",
      "outputIndex": 2,
      "outputGlobalIndex": 48678798,
      "outputCreatedAt": 1559891,
      "outputSettledAt": 1559893,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(126,-119,-126,-122,21,45,53,37,-18,-76,-34,-118,29,-125,58,61,92,-95,-6,120,-71,10,-24,61,-102,15,4,-63,66,31,66,-68)\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(108,-95,21,91,-21,51,44,-107,-42,-43,66,80,-117,95,-43,-43,56,7,-116,-16,49,-51,-113,124,113,107,-15,-118,-39,-64,-40,-46,126,-25,-8,52,64,61,-38,-32,79,110,84,127,-105,-74,-57,19,3,61,70,118,102,123,-28,-112,18,29,-58,89,-11,35,5,66)",
      "ergoTreeScript": "{\n  val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\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 coll3 = Coll[Byte]()\n  val opt4 = getVar[Coll[Byte]](1.toByte)\n  val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n  val coll6 = placeholder[Coll[Byte]](3)\n  val coll7 = coll6.slice(32, 64)\n  val coll8 = placeholder[Coll[Byte]](0)\n  val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n  val coll10 = placeholder[Coll[Byte]](2)\n  val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n        val tuple15 = tuple13._2\n        tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n      }) }\n  val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n  val coll13 = Coll[Byte](\n    91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n  )\n  val b14 = getVar[Byte](0.toByte).get\n  val func15 = {(box15: Box) => box15.tokens(1) }\n  val i16 = INPUTS.indexOf(SELF, 0)\n  val func17 = {(l17: Long) =>\n    if (l17 < 128L) { 1 } else {\n      if (l17 < 16384L) { 2 } else {\n        if (l17 < 2097152L) { 3 } else {\n          if (l17 < 268435456L) { 4 } else {\n            if (l17 < 34359738368L) { 5 } else {\n              if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n            }\n          }\n        }\n      }\n    }\n  }\n  sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n            val coll20 = blake2b256(SELF.propositionBytes)\n            val box21 = func1((OUTPUTS, coll20))(0)\n            val coll22 = CONTEXT.dataInputs\n            val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n            val coll24 = opt4.getOrElse(coll3)\n            val coll25 = func1((INPUTS, coll20))\n            val l26 = func5(coll25)\n            val box27 = func2((OUTPUTS, coll7))(0)\n            val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-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), Coll[Byte](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), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n            val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n            val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n            val l31 = func11((coll25, coll10))\n            val coll32 = Coll[Box](box21)\n            val l33 = func11((coll32, coll10))\n            val l34 = func11((coll25, coll29))\n            val l35 = func11((coll32, coll29))\n            val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n                val coll38 = tuple36._1\n                (coll38 != coll10) && (coll38 != coll29)\n              }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n            val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n                val coll39 = tuple37._1\n                (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n              })\n            anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n                    val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.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), coll13), coll24)\n                    val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n                    val bool42 = coll10 == coll29\n                    allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n                  )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n                    val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n                    allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n                  )} else { false } }(b14)))\n          )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](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(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n            val coll20 = blake2b256(SELF.propositionBytes)\n            val coll21 = func1((INPUTS, coll20))\n            val coll22 = func1((OUTPUTS, coll20))\n            val l23 = func5(coll21)\n            allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n          )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n                val box22 = OUTPUTS(i16)\n                val l23 = box22.value\n                val l24 = SELF.value\n                val coll25 = box22.propositionBytes\n                val coll26 = SELF.bytesWithoutRef\n                val coll27 = SELF.propositionBytes\n                val i28 = SELF.creationInfo._1\n                val coll29 = box22.bytesWithoutRef\n                val i30 = box22.creationInfo._1\n                allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n              )} }((Coll[Byte](-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), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "a650291cd343d511a435b8720476736fcaf3e6c87f977b4e8123bcff666543be",
          "index": 0,
          "amount": 955,
          "name": "Ergo DevDAO",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [
    {
      "boxId": "7de36a93ca6c228bfd697de21ee99ca785571752c04bcb9b3d366d63983e067c",
      "value": 1000000000,
      "index": 0,
      "outputBlockId": "5115d96676cf8bead4c6a91614957d3722796ea67690a1f7954d8499b608b587",
      "outputTransactionId": "c83eefcb05036e003ed760d8d837628e5f06b22a85b2d5cd6e99c884181b4362",
      "outputIndex": 1,
      "ergoTree": "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",
      "address": "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",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "6494292909325aa7155ea9309605bb03c6f9d17521128cb49f4c1109d54b50719b06072000",
          "sigmaType": null,
          "renderedValue": null
        }
      }
    },
    {
      "boxId": "eb4f751ca0c605dc3f1a3387658dffd7c4028d9b7e92c4508584cf50b29c382f",
      "value": 2000000,
      "index": 1,
      "outputBlockId": "4ad5cca07a183dd6453cf431076b40b86acba873c920f8cf7408358e84d4ec25",
      "outputTransactionId": "849efa284c55e528a8362ea5bfe710d4681f4e644cd6191d9827b029ee19e32c",
      "outputIndex": 0,
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      "address": "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",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "10020602",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[3,1]"
        },
        "R5": {
          "serializedValue": "1104a689a7a1fa65040004",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1751576273491,2,0,2]"
        },
        "R6": {
          "serializedValue": "64daed54ace9bb8dcb4942faffaf3e91d6e76b3b8b15601996fbc7da29260c416302072000",
          "sigmaType": null,
          "renderedValue": null
        },
        "R7": {
          "serializedValue": "0e13426f756e74696573202d20447573656b205632",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "426f756e74696573202d20447573656b205632"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "8c472a679c3d06a9ad1c5a74bfdde9dc501376b0add2bcfc60dbc2d411408dd4",
      "transactionId": "ad85c7d9a0b012095b3d6c1e7d3eb7d95caf6836cf944791f63fcf4f76c508af",
      "blockId": "4ad5cca07a183dd6453cf431076b40b86acba873c920f8cf7408358e84d4ec25",
      "value": 500001000000,
      "index": 0,
      "globalIndex": 48746482,
      "creationHeight": 1562859,
      "settlementHeight": 1562861,
      "ergoTree": "0008cd0216133993bbc54c0d48a21634a7d2632b8c92d744d565839dc39c912ef406e0d9",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(161339,3828ae,...)))}",
      "address": "9egnPnrYskFS8k1gYiKZEXZ2bhP9fvX9GZvsG1V3BzH3n8sBXrf",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "04b683c81b104a154aa95a3f91d3c3763ef07b2a5bc2dea6ed65ad295652d6f3",
      "mainChain": true
    },
    {
      "boxId": "8ce3abebb3a1cca7f0a9a239b21b84f9ab26e5b7ecdbf259321b5e455e87186e",
      "transactionId": "ad85c7d9a0b012095b3d6c1e7d3eb7d95caf6836cf944791f63fcf4f76c508af",
      "blockId": "4ad5cca07a183dd6453cf431076b40b86acba873c920f8cf7408358e84d4ec25",
      "value": 1000000,
      "index": 1,
      "globalIndex": 48746483,
      "creationHeight": 1562859,
      "settlementHeight": 1562861,
      "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": "3236a546bfdfb4739d99cd750be77d351364a076c7d41b9d41b3cec400291a67",
      "mainChain": true
    },
    {
      "boxId": "5dd6fca8d79372ade55014cacb7c687fec90468e17f072836c7b3b04523f934b",
      "transactionId": "ad85c7d9a0b012095b3d6c1e7d3eb7d95caf6836cf944791f63fcf4f76c508af",
      "blockId": "4ad5cca07a183dd6453cf431076b40b86acba873c920f8cf7408358e84d4ec25",
      "value": 1855907000000,
      "index": 2,
      "globalIndex": 48746484,
      "creationHeight": 1562859,
      "settlementHeight": 1562861,
      "ergoTree": "10040e207e898286152d3525eeb4de8a1d833a3d5ca1fa78b90ae83d9a0f04c1421f42bc0e201b4b8b789fdd4a34c5f1cf73b4d99a5cacb8ccba75265f6edf4950893b162f070e201fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad4890e406ca1155beb332c95d6d542508b5fd5d538078cf031cd8f7c716bf18ad9c0d8d27ee7f834403ddae04f6e547f97b6c713033d4676667be490121dc659f5230542d811d601d901013c0c630eb58c720101d901036393cbc272038c720102d602d901023c0c630eb58c720201d9010463aedb63087204d901064d0e938c7206018c720202d603830002d604e3010ed605d901050c63b072050500d9010741639a8c720701c18c720702d6067303d607b472060440048001d6087300d609d9010963e4c672090464d60a7302d60bd9010b3c0c630eb0dc0c0f8c720b0101d9010d63db6308720d0500d9010d414d0ed801d60f8c720d029a8c720d0195938c720f018c720b028c720f020500d60cd9010c32b4e4720c04020442d60d832002025b02cf02f102020225024302660278020c02d50219021202570205020a026e02d3023a02c502d1022e02ef020e02300241023902ed025d0298021f024b02fad60ee4e30002d60fd9010f63b2db6308720f040200d610dc0c1aa402a70400d611d9011105958f72110580020402958f7211058080020404958f721105808080020406958f72110580808080020408958f721105808080808002040a958f72110580808080808002040c958f7211058080808080808002040e958f72110580808080808080800204100412d197830401dad901120295ec93721202039372120204d812d614cbc2a7d615b2da7201018602a57214040000d616db6501fed617b2da720201860272167301040000d618e572047203d619da7201018602a47214d61ada7205017219d61bb2da7202018602a57207040000d61cdc640bda720901b2da7202018602721672080400000283040e8320020289022e026f024702a1020d025c029002b8027a02d402860233025502ce02ad020002c302e202980232021702ee021502530232025302cd029a0260022502c2832002024f02d802b002d602d9028202420272026f025702b302df02a6028602120267029202b802e50205026e021d025102b602e9020d0268028002cf022d02cd02c583200202b002b9020702ab02af02ad028d02ff02ce022f029f021d02fa0215023502c0022202dd02a00253026602f402fb02d2027f0258021d0213022f024b022302f683200202b802c3022c020b029e024202cc028602d0023002b20261028e025a020602c002d202eb022b02a00264021f02090206028502b9028502ed02ab02100295026fe5e3020e7203d61ddad9011d32b4e4721d040c044c01b2721c040600d61e7cb4e4b2721c04040004020412d61fda720b0186027219720ad6208301637215d621da720b0186027220720ad622da720b0186027219721dd623da720b0186027220721dd624afb5db63087215d901244d0ed801d6268c722401ed947226720a947226721dd901244d0e928c722402da720b01860272198c722401d625afdc0c0f721901d9012563db63087225d901254d0ed801d6278c722501ec937227720aaedb63087215d901284d0e938c722801722797830201dad9012602959372260203d803d628dc640bda72090172170283040e8320020222025e023f02c502d1028902f5024702d902c6022602be02bd02c602710239028b026c0200027c0278023d02c4027f0290023f022402bf027f02340284027983200202bc024a025a02b902e4025a02b7024b027902fa02ec02bf02670249026c02c202bf028c022b020e025502db02e802ac02cf02c3029d021402890211027402908320020276027c02aa028002b9028e0249026a02d802a902f6028902c40241020a02e402530232027f020f029502e90250028402c002ae0220026302500279023b0277720d7218d6299a9c7cb4e4b2722804000004020412dad9012963b2e4c67229051104040001721b0502d62a93720a721d9683070192c1721599721a7cb4e4b272280406000402041292722199721f9a9a72297cb4e4b272280402000402041295722a721e050095722a0101927223997222721e7224722592da720b018602830163b2b5a5d9012b6393cbc2722bb4e4b2722804040004020442040000720a722993cbc2b2a4040200da720c01b2721c040200010001720edad9012602959372260204d801d628dc640bda72090172170283020e83200202ec02f202d0024b02ae024802a0020a028a026e024902c002560272026302c902f502d2023f022602c80223025802a1027602ab02d102f0022102d802b10230720d72189683070192c1721599721a7cb4e4b272280402000402041292722199721f7cb4e4b27228040000040204129593720a721d010192722372227224722593cbc2b2a4040200da720c01b2721c040000938cda720f01721b028cda720f01b2da7202018602a4720704000002010001720e010001720edad9011202959372120209e6b2dc640bda720901b2da7202018602db6501fe72080400000283010ecbb3831c020269026d022e0270026102690264026502690261022e0263026f026e027402720261026302740273022e0261026302740269026f026e022ec2b2da7202018602a4b4720604000440040000e47204040000010001720edad901120295937212020ad804d614cbc2a7d615da7201018602a47214d616da7201018602a57214d617da72050172159683050192b17215040a93b172160402afdb6308b27216040000d901184d0e93da720b01860272158c7218018c72180290997217da7205017216058092f401927217058092f401010001720edad9011202959372120207dad901143c0e6395927210b1a50100d809d616b2a5721000d617c17216d618c1a7d619c27216d61ac4a7d61bc2a7d61c8cc7a701d61dc47216d61e8cc772160196830401927217997218058092f40193cb7219da720c01b2dc640bda7209018c7214020283010e8c721401e57204720304000093b4721a9a9ada7211017218b1721bda7211017e721c05b1721ab4721d9a9ada7211017217b17219da7211017e721e05b1721d978302019299721e721c0480c33d94721b721901860283200202c702c5023702e602c602350293020e02cb024a02ce029502a50249022602b302ab02770269028d029f0249022202f002b102c5028e02a8027102560248023bb2da7202018602db6501fe7208040000010001720e",
      "ergoTreeConstants": "0: Coll(126,-119,-126,-122,21,45,53,37,-18,-76,-34,-118,29,-125,58,61,92,-95,-6,120,-71,10,-24,61,-102,15,4,-63,66,31,66,-68)\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(108,-95,21,91,-21,51,44,-107,-42,-43,66,80,-117,95,-43,-43,56,7,-116,-16,49,-51,-113,124,113,107,-15,-118,-39,-64,-40,-46,126,-25,-8,52,64,61,-38,-32,79,110,84,127,-105,-74,-57,19,3,61,70,118,102,123,-28,-112,18,29,-58,89,-11,35,5,66)",
      "ergoTreeScript": "{\n  val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\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 coll3 = Coll[Byte]()\n  val opt4 = getVar[Coll[Byte]](1.toByte)\n  val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n  val coll6 = placeholder[Coll[Byte]](3)\n  val coll7 = coll6.slice(32, 64)\n  val coll8 = placeholder[Coll[Byte]](0)\n  val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n  val coll10 = placeholder[Coll[Byte]](2)\n  val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n        val tuple15 = tuple13._2\n        tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n      }) }\n  val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n  val coll13 = Coll[Byte](\n    91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n  )\n  val b14 = getVar[Byte](0.toByte).get\n  val func15 = {(box15: Box) => box15.tokens(1) }\n  val i16 = INPUTS.indexOf(SELF, 0)\n  val func17 = {(l17: Long) =>\n    if (l17 < 128L) { 1 } else {\n      if (l17 < 16384L) { 2 } else {\n        if (l17 < 2097152L) { 3 } else {\n          if (l17 < 268435456L) { 4 } else {\n            if (l17 < 34359738368L) { 5 } else {\n              if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n            }\n          }\n        }\n      }\n    }\n  }\n  sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n            val coll20 = blake2b256(SELF.propositionBytes)\n            val box21 = func1((OUTPUTS, coll20))(0)\n            val coll22 = CONTEXT.dataInputs\n            val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n            val coll24 = opt4.getOrElse(coll3)\n            val coll25 = func1((INPUTS, coll20))\n            val l26 = func5(coll25)\n            val box27 = func2((OUTPUTS, coll7))(0)\n            val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-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), Coll[Byte](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), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n            val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n            val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n            val l31 = func11((coll25, coll10))\n            val coll32 = Coll[Box](box21)\n            val l33 = func11((coll32, coll10))\n            val l34 = func11((coll25, coll29))\n            val l35 = func11((coll32, coll29))\n            val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n                val coll38 = tuple36._1\n                (coll38 != coll10) && (coll38 != coll29)\n              }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n            val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n                val coll39 = tuple37._1\n                (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n              })\n            anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n                    val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.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), coll13), coll24)\n                    val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n                    val bool42 = coll10 == coll29\n                    allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n                  )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n                    val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n                    allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n                  )} else { false } }(b14)))\n          )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](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(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n            val coll20 = blake2b256(SELF.propositionBytes)\n            val coll21 = func1((INPUTS, coll20))\n            val coll22 = func1((OUTPUTS, coll20))\n            val l23 = func5(coll21)\n            allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n          )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n                val box22 = OUTPUTS(i16)\n                val l23 = box22.value\n                val l24 = SELF.value\n                val coll25 = box22.propositionBytes\n                val coll26 = SELF.bytesWithoutRef\n                val coll27 = SELF.propositionBytes\n                val i28 = SELF.creationInfo._1\n                val coll29 = box22.bytesWithoutRef\n                val i30 = box22.creationInfo._1\n                allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n              )} }((Coll[Byte](-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), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
      "address": "guXrqWFapBNMLqp4V3MjoeSWAhGumHHypTZJRFjahh2zRGPJNDDQrxYPckCESjcd4tQuxAii5zVr6AbS7Z3UJySQrsoijWUTfskQpg41U2KvhoA8MTbeyc2mKGNHATHkaLSvWrqG28wrXjNvbneDFfeWEFjnpNFk9uZh9Xzt6gwGy1c54jNJjjC1FoqMNULvBofeGzfnyEoz2Ra5GD1sE6Vp3dr3Mq1nYmBcm9fUY4YeifKns9tmPfpNNtZrRxSju3jKpHs1bSEV3gjpzsZLEujjfBusKZFiFxnHwKcZ2LjCD7v5Bfm9URgSfWT2mbiBogmUVesL6HMUa4NxNUGByNnzXFHZjQGrkuMyKEKJfyF2yds8twym6bPa1amZdE4pfS95nATSjKBSsRfCFMUGuF25R7zXb4VUyZpKh3c19rVEMMfuy27LKojtaFHbk2fW6qShMNhiyqGJN1QzxPrXJezD9hSQ2o1gYucyDAjWyGDnvFeTPxRD64WdJ8usNXx98tZoQYqkecTj1Wtsg773GaprwRpxn9XRFNoDT1Ku7Sfv6N4PzXqT7JdysqXB6Q2dERJ1Bfb7G5LZxoMTuz3z4GL9zoQnngS8tisbGTU7MwSSwkoAsqmDuWbJr3oqQysqmLMdA3CCCZXeZNytJ7ADAYR79hBMQvkv2WcSSEhijxbdaMDehb4NU9d2oNYKzMChHSzMk2apKEPst3Fsjwppbtn2Whqkotwue5qXZnMgNo1mVQgctzaPMNE25f8nwzcEs6GgHY5JMWuXQLi6k7QtH3rn2y6J1TcodLHAt5hNefQdzLcoaGVeKM8yZTKJ5T6AXMsLJTko2vwzgN6g6KGhEe2em3e1ey7HQM7QhQy9gTu4zK9DretNjofCtGEq9BeqghCYrJGHkG8DKRoHYHh8qPtLbMxNjThPWTajxxinKJ5GDD2KydRPjBo6Ws4fDp9KYF8uGjgsrUfbvojYrEQhcGmBWcYsSctZQarn9NHHdWUTZQjgiUEHLUtaqVmdedjjszaavskJt9hBkSauhxRL8oUTdMwUUDLXQtY13iKXzdsQdDAPfGK6oanwp6taoZd2FTkM7PpSgCkVnPPrg8NRCmGjEwxxLZ9B9NSGRX8CTHpmrMg1L9wJJGXv522NgMuDpwysknKXRheKrwQqMKj93nHcVKmRzbvEsvUrov25Zio89JEdkDfNx8U7twihHHegbdQSva7FoMqWGrfufo3MgumKFXtVCSHLqPE4NjUXtuxxvL6zpHeZ7G5xLD1QCfM6AraGmQiQ29dhDaNY5hjAQW2wKwV2kfnRip1PuFg8m9eE8KbsRhkgWbSNZcBRAQzSrZkSGdZf9gJAigezyjAqcNiYHzg857WXXZGVYWcXAn87PbL4ptUZcSGNWobJ6RKKPQoSPva999b8wEYULtBreq6UPte6dQPB8PX9GqYNfsiCh48WCux6g65kXzLZr9WjuTRKj7qec5oKM8nM6xUUM6mxBecHjpgRuk4rrTQZ7buigQe91yMk4ZkVeCoVHEDT13BaReEhXFo2LCCoQ5Qb2jLcR8QUAtpM73gmm4QtAw4DdzgG5SxhtCtFCmoNsqzNM52WfWy6eXK58jSWaeY6H2fmLq9ZZQ9G8zmJKSctDep41zmbXWURwdtrV3xmfptB6cYYM39QMZsFiMRvYTiPhCDjdj1kdGVLkgFdw6W4Ae9jxugEALbFV38WSyXXvrUaefpmucE6KHW8pcWNXSfuzqy6mTeieKNLbiQv7SD2xhSjCdSo3uVW1ohFyKxXc7ynhkos3KLboP5cNH999gDEdKbVXecDMxbbiWhjUZerVt1Kz9rjjkj9tpbe8YAVFTbTaZBRsAXwVqh3kPUnnaZ13HQM4Q6sEUH6HuWeL4Yaque4GAixNkX9mr6Tgw4F9nPBU3qmkiaFbx8hhMKa2qydak5enJ5dHNnP2rpZP2tz26diihdLxBop9wofHDK5b1FfP89f3GjtCZazCLGYyxL27oGKbbi6v3rRLYDqExL3MMi2jh9T6S2JWmJAQn5F9HA8PP1gCox7M1nq4v2N4hA7JDo5WggRdix3j2zhqBfiuR9LkdKJP8ti8nFZviSYG3wPV7D763Wnhh64vGYfCvfUyh4jHGopKtSUztWDPHDvvYBzq9MhV5KzQJ9mRGUCviBUNuavius9dCBMmSNxXV4HLDbXey4QWr8cVpTJ3eizHZH1VeYYKSB8DsMPpTBuUk5a8DyJGvXjXXkRK1X1LvA53sxp2agDw1SHhKkVnHdcFLtQRwYSyWAWCzx5NZaSngsFneiiD6jJ3PZn4ukBtQUGGXJDmApujWUF3bEeZppHAm4RBFDUWAcLv6dwhXQCJ4CwxkeAGLAKGCa16Y3TVx5LSnu8ctj2nqedmi4yRQz7zNWu3XqpqsgnmsSvuJe1YywnbitdAn4g11LSJmsnEAFkWgxBM9mGRB8ezb7rEc9Xb1yq3VFt4WYLM8vr83aXMav3fbExqkjNCgnGKfcXwdu4egqoZo8HWfeWYRwfwm14sRwkQXXQyMY1cZ62TLKDEa2pWvD2mi5ErmcczytPchNH8tKMzs1AdZKHTfn7xGKpLw2jvHSTGQtK6nk5VNs9xmQmYfmd8hVqbe2AxxxaVE1EcpFVZaBzLfJVa2oY6E21Lp3zbVniNWZkNGuUzFR34AG43wuJTK3KpGT2YVwpkpCAd1nKNxGeHDFvWGHYBBKvabJrATiX6Z9bbgvSVcuXKqpejPXbgiiNYfnwQhDD9dAzyUbsZkSedvZV76aCYqigd9H7iuRqcjhre2dvo2QCedp1hdJFp7M4XzK7urAPN53tJy5bQbCmjAB3UPUz46QtQ4HKxTkdQkz177a3ny6B5FgXnzYUUPoq7tEGeP6YDGCT7U4MS8etwrce4gPYQdm58HHysMKim1EM7cfgwyASN5JF2T1uuctfQBerMKCdGuZ5wAdegW7yJDkBsVH37t15HFkjDAggHn6EeQqi3SRqr7obZWgWHGbzcuKhtzNCtdX1o4E43iixKNfGsthozEwdTRA4AWGSrP2HxmaWyabXF3kyteivaK4gJZ9c8STHaLbwgLr1tVjZwBJzFjXiGTcK8uadUBPktwFajWAp77QyrThi6zqEPvGRmcGUN236He5srA6RQ2MX1eeXnhWnz68qkvy9JKBDpJzqA8XMgbYtrPkopAYfJC5EnfoY11w8vcfmzSBXsow7JtYtnKvhMgvFD4DBo62EJM8i",
      "assets": [
        {
          "tokenId": "a650291cd343d511a435b8720476736fcaf3e6c87f977b4e8123bcff666543be",
          "index": 0,
          "amount": 955,
          "name": "Ergo DevDAO",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "3716340bb89b3f0a553d000cc242afd56a90d94c0a4805087d2889242813710c",
      "mainChain": true
    }
  ],
  "size": 3431,
  "isUnconfirmed": false
}