Ad
Inputs (3)
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
1
Output transaction:
Settlement height:
Value:
0.89239164 ERG
Tokens:
Loading assets...
Outputs (4)
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
5
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent in transaction:
Settlement height:
Value:
0.89129164 ERG
Tokens:
Loading assets...
Transaction Details
Status: Confirmed
Size: 2.21 KB
Received time: 1/12/2026 06:29:07 PM
Included in blocks: 1,698,375
Confirmations: 73,998
Total coins transferred: 0.89439164 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000485 ERG
Raw Transaction Data
{
  "id": "fa06dc55ea79ba724d1782b48dbac05f6e61363ebb022b2b2cf91bc500da8e75",
  "blockId": "447ba83f77e9dec35682fc46c3da320b8668d07aede9cc24ade8106426142eb1",
  "inclusionHeight": 1698375,
  "timestamp": 1768242547341,
  "index": 21,
  "globalIndex": 10134688,
  "numConfirmations": 73998,
  "inputs": [
    {
      "boxId": "bbbca523036185a1ef8eae98b05651bad26cc2c9c264235ce0095d6837f76de9",
      "value": 1000000,
      "index": 0,
      "spendingProof": "a5c04d9b7a8a50f23b267b85b40edcd1d71dc8a83fbbbef630dd3e205400a2d2414f4bb3d03d2687cadbfeb17f35f586bcd05ab9d328292c",
      "outputBlockId": "11ba737e4f8431dbf13dae57a3fdb62d6d5d6288c8da33f5a63ddacd61a71fa0",
      "outputTransactionId": "ed4ca685fb3bc6a6bdd4b2b2e39cc1a655dad926661c57d045640597860edb6b",
      "outputIndex": 0,
      "outputGlobalIndex": 52929350,
      "outputCreatedAt": 1698370,
      "outputSettledAt": 1698372,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(3,119,75,87,95,-98,29,-103,49,-2,-104,-124,71,49,118,-34,109,19,-84,-57,-62,-120,30,-8,111,74,-123,-101,-6,-20,29,-78)\n1: 0\n2: Coll(-65,-122,-35,24,-60,88,124,-14,-74,117,-80,126,44,-32,-26,-118,-31,-2,87,53,-62,-85,-26,108,-16,52,-91,11,20,-12,-64,110)\n3: 1\n4: 0\n5: 0\n6: 2\n7: 1\n8: 0\n9: 3\n10: 1000000\n11: 50000\n12: 1000000\n13: 2\n14: Coll(0,8,-51,2,90,-56,-85,24,63,-3,-29,96,104,96,49,32,-80,10,-51,-15,65,-71,31,-28,-32,-64,-58,-43,98,-75,-14,78,30,44,-62,-47)\n15: 0\n16: 0\n17: 0\n18: true\n19: 0\n20: Coll(25,-72,3,14,5,0,5,0,4,0,14,32,58,-108,98,24,98,-10,116,84,-53,-35,97,62,-45,-90,68,-126,-71,-33,-29,9,60,97,-126,53,107,-92,-12,-95,68,17,-9,-107,4,0,4,0,4,0,4,2,1,0,5,0,5,0,4,0,4,2,1,1,-40,4,-42,1,-39,1,1,99,-80,-75,-37,99,8,114,1,-39,1,3,77,14,-109,-116,114,3,1,-28,-58,-89,5,14,115,0,-39,1,3,65)\n21: 1\n22: 0\n23: false\n24: true\n25: Coll(0,8,-51)\n26: 3\n27: 0\n28: 3\n29: false\n30: 3\n31: 5\n32: 5\n33: 0\n34: 0\n35: 3\n36: 0\n37: 3\n38: false\n39: 3\n40: false\n41: 1\n42: 1\n43: 0\n44: -1\n45: false\n46: true\n47: 0\n48: 10\n49: 4\n50: 1000000\n51: 0\n52: 0\n53: 0\n54: 0\n55: 0\n56: 0\n57: 0\n58: 0\n59: 0\n60: true\n61: 0\n62: 0\n63: true\n64: false\n65: false\n66: 0\n67: 0\n68: 0\n69: 0",
      "ergoTreeScript": "{\n  val tuple1 = SELF.R6[(Coll[Byte], Coll[Byte])].get\n  val coll2 = tuple1._2\n  val bool3 = coll2 != Coll[Byte]()\n  val coll4 = placeholder[Coll[Byte]](0)\n  val coll5 = SELF.tokens(placeholder[Int](1))._1\n  val coll6 = INPUTS.filter({(box6: Box) =>\n      val coll8 = blake2b256(box6.propositionBytes)\n      ((coll8 == coll4) || (coll8 == placeholder[Coll[Byte]](2))) && (box6.R6[Coll[Byte]].get == coll5)\n    })\n  val coll7 = SELF.R9[Coll[Coll[Byte]]].get\n  val coll8 = coll7(placeholder[Int](3))\n  val func9 = {(box9: Box) =>\n    if (coll8.size == placeholder[Int](4)) { box9.value } else {\n      box9.tokens.filter({(tuple11: (Coll[Byte], Long)) => tuple11._1 == coll8 }).fold(\n        placeholder[Long](5), {(tuple11: (Long, (Coll[Byte], Long))) => tuple11._1 + tuple11._2._2 }\n      )\n    }\n  }\n  val coll10 = SELF.R8[Coll[Long]].get\n  val l11 = coll10(placeholder[Int](6))\n  val l12 = coll10(placeholder[Int](7))\n  val l13 = coll6.fold(placeholder[Long](8), {(tuple13: (Long, Box)) => tuple13._1 + func9(tuple13._2) }) + func9(SELF) - l12\n  val coll14 = SELF.R7[Coll[Coll[Byte]]].get\n  val l15 = l13 * coll10(placeholder[Int](9)) / placeholder[Long](10) * coll14.size.toLong\n  val l16 = l13 * placeholder[Long](11) / placeholder[Long](12)\n  val coll17 = coll7(placeholder[Int](13))\n  val coll18 = placeholder[Coll[Byte]](14)\n  val bool19 = if (l16 > placeholder[Long](15)) {\n    OUTPUTS.filter({(box19: Box) => box19.propositionBytes == coll18 }).fold(\n      placeholder[Long](16), {(tuple19: (Long, Box)) => tuple19._1 + func9(tuple19._2) }\n    ) - INPUTS.filter({(box19: Box) => box19.propositionBytes == coll18 }).fold(\n      placeholder[Long](17), {(tuple19: (Long, Box)) => tuple19._1 + func9(tuple19._2) }\n    ) >= l16\n  } else { placeholder[Boolean](18) }\n  val bool20 = if (l15 > placeholder[Long](19)) {(\n    val coll20 = OUTPUTS.filter({(box20: Box) => box20.propositionBytes == placeholder[Coll[Byte]](20) })\n    if (coll20.size == placeholder[Int](21)) {(\n      val box21 = coll20(placeholder[Int](22))\n      ((func9(box21) >= l15) && (box21.R4[Coll[Coll[Byte]]].get == coll14)) && (box21.R5[Coll[Byte]].get == coll8)\n    )} else { placeholder[Boolean](23) }\n  )} else { placeholder[Boolean](24) }\n  val i21 = coll17.size\n  val coll22 = placeholder[Coll[Byte]](25)\n  val prop23 = if (if (i21 >= placeholder[Int](26)) { coll17.slice(placeholder[Int](27), placeholder[Int](28)) == coll22 } else { placeholder[Boolean](29) }) {\n    proveDlog(decodePoint(coll17.slice(placeholder[Int](30), i21)))\n  } else { sigmaProp(INPUTS.exists({(box23: Box) => box23.propositionBytes == coll17 })) }\n  val coll24 = INPUTS.filter({(box24: Box) => (blake2b256(box24.propositionBytes) == coll4) && (box24.R5[Coll[Byte]].get == coll2) })\n  val prop25 = if (bool3) {\n    if (HEIGHT.toLong >= coll10(placeholder[Int](31)) + placeholder[Long](32)) { prop23 } else { if (coll24.size > placeholder[Int](33)) {(\n        val coll25 = coll24(placeholder[Int](34)).R4[Coll[Byte]].get\n        val i26 = coll25.size\n        if (if (i26 >= placeholder[Int](35)) { coll25.slice(placeholder[Int](36), placeholder[Int](37)) == coll22 } else { placeholder[Boolean](38) }) { proveDlog(decodePoint(coll25.slice(placeholder[Int](39), i26))) } else { sigmaProp(INPUTS.exists({(box27: Box) => box27.propositionBytes == coll25 })) }\n      )} else { sigmaProp(placeholder[Boolean](40)) } }\n  } else { prop23 }\n  sigmaProp(SELF.R4[Int].get == placeholder[Int](41)) && if (bool3) {(\n    val coll26 = coll6.filter({(box26: Box) => box26.R5[Coll[Byte]].get == coll2 })\n    if (coll26.size == placeholder[Int](42)) {(\n      val box27 = coll26(placeholder[Int](43))\n      if ((({(box28: Box) => box28.R9[Coll[Long]].get.fold((placeholder[Long](44), placeholder[Boolean](45)), {(tuple30: ((Long, Boolean), Long)) =>\n                val tuple32 = tuple30._1\n                val l33 = tuple30._2\n                if (tuple32._2) { tuple32 } else { if (blake2b256(box28.R7[Coll[Byte]].get.append(SELF.R5[Coll[Byte]].get).append(longToByteArray(l33)).append(box28.R8[Coll[Byte]].get).append(box28.R4[Coll[Byte]].get).append(tuple1._1)) == box28.R5[Coll[Byte]].get) { (l33, placeholder[Boolean](46)) } else { tuple32 } }\n              }) }(box27)._2 && (func9(box27) >= l11)) && (box27.creationInfo._1.toLong < coll10(placeholder[Int](47)))) && (\n        box27.R9[Coll[Long]].get.size.toLong <= placeholder[Long](48)\n      )) {(\n        val coll28 = box27.R4[Coll[Byte]].get\n        val l29 = l13 * coll10(placeholder[Int](49)) / placeholder[Long](50)\n        val l30 = l13 - l29 - l15 - l16\n        val bool31 = l30 < l11\n        prop25 && sigmaProp(\n          (\n            (\n              (\n                (\n                  OUTPUTS.filter({(box32: Box) => box32.propositionBytes == coll28 }).fold(\n                    placeholder[Long](51), {(tuple32: (Long, Box)) => tuple32._1 + func9(tuple32._2) }\n                  ) - INPUTS.filter({(box32: Box) => box32.propositionBytes == coll28 }).fold(\n                    placeholder[Long](52), {(tuple32: (Long, Box)) => tuple32._1 + func9(tuple32._2) }\n                  ) >= if (bool31) { l13 } else { l30 }\n                ) && OUTPUTS.exists(\n                  {(box32: Box) =>\n                    ((box32.propositionBytes == coll28) && (box32.tokens.size > placeholder[Int](53))) && (box32.tokens(placeholder[Int](54))._1 == coll5)\n                  }\n                )\n              ) && (\n                OUTPUTS.filter({(box32: Box) => box32.propositionBytes == coll17 }).fold(\n                  placeholder[Long](55), {(tuple32: (Long, Box)) => tuple32._1 + func9(tuple32._2) }\n                ) - INPUTS.filter({(box32: Box) => box32.propositionBytes == coll17 }).fold(\n                  placeholder[Long](56), {(tuple32: (Long, Box)) => tuple32._1 + func9(tuple32._2) }\n                ) >= l12 + if (bool31) { placeholder[Long](57) } else { l29 }\n              )\n            ) && if (if (bool31) { placeholder[Long](58) } else { l16 } == placeholder[Long](59)) { placeholder[Boolean](60) } else { bool19 }\n          ) && if (if (bool31) { placeholder[Long](61) } else { l15 } == placeholder[Long](62)) { placeholder[Boolean](63) } else { bool20 }\n        )\n      )} else { sigmaProp(placeholder[Boolean](64)) }\n    )} else { sigmaProp(placeholder[Boolean](65)) }\n  )} else {\n    prop25 && sigmaProp(\n      (\n        (\n          (\n            OUTPUTS.filter({(box26: Box) => box26.propositionBytes == coll17 }).fold(\n              placeholder[Long](66), {(tuple26: (Long, Box)) => tuple26._1 + func9(tuple26._2) }\n            ) - INPUTS.filter({(box26: Box) => box26.propositionBytes == coll17 }).fold(\n              placeholder[Long](67), {(tuple26: (Long, Box)) => tuple26._1 + func9(tuple26._2) }\n            ) >= l13 + l12 - l16 - l15\n          ) && OUTPUTS.exists(\n            {(box26: Box) =>\n              ((box26.propositionBytes == coll17) && (box26.tokens.size > placeholder[Int](68))) && (box26.tokens(placeholder[Int](69))._1 == coll5)\n            }\n          )\n        ) && bool19\n      ) && bool20\n    )\n  }\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "b09da2f796090fb0a11216b73410d2899f9c2ed7d05e3197a8268e1ba356f54d",
          "index": 0,
          "amount": 1,
          "name": "TEST V4",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
          "index": 1,
          "amount": 500,
          "name": "CAT",
          "decimals": 2,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "0e08d0b02b05dabc25f9",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "d0b02b05dabc25f9"
        },
        "R6": {
          "serializedValue": "3c0e0e2035aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f2120d9925b96cebed2c0a11487f7ad0633344e9e13f4bace51b297c8bbff30da2409",
          "sigmaType": "(Coll[SByte], Coll[SByte])",
          "renderedValue": "[35aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21,d9925b96cebed2c0a11487f7ad0633344e9e13f4bace51b297c8bbff30da2409]"
        },
        "R8": {
          "serializedValue": "1107d2a8cf01e807c801a09c01a0c21ef2a8cf011e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1698345,500,100,10000,250000,1698361,15]"
        },
        "R7": {
          "serializedValue": "1a0120758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9]"
        },
        "R9": {
          "serializedValue": "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",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[7b227469746c65223a2254455354205634222c226465736372697074696f6e223a22222c22696d61676555524c223a22222c2263726561746f72546f6b656e4964223a2237353865623739363635323234343932633866623834396130383735316434316364353937346137616631303939653535353866353432346133383231666339222c22736572766963654964223a2233356161313131383663313864336530346638313635363234383231336131613363343365383961363730343537363332383765363434646236306333663231222c227061706572223a22222c22696e64657465726d69736d496e646578223a2234227d,aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71,0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7]"
        },
        "R4": {
          "serializedValue": "0402",
          "sigmaType": "SInt",
          "renderedValue": "1"
        }
      }
    },
    {
      "boxId": "60a26bcddf7c37ef4c95e42c824df0c9265c56b1d5a4033c411f34d62bd6cafa",
      "value": 1000000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "9f71ae954bdeeedbfa5962ee33f5c1035a9994e0a73570566a7883917fb5f7e5",
      "outputTransactionId": "324d3448cde44c7c2dec0c7e6bc254db9ffdc3d85c725cf674b5d246faae0c2d",
      "outputIndex": 0,
      "outputGlobalIndex": 52928571,
      "outputCreatedAt": 1698342,
      "outputSettledAt": 1698344,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(0,8,-51)\n2: 1\n3: 0\n4: 1\n5: 0\n6: 1\n7: 0\n8: 1\n9: 0\n10: 1\n11: false\n12: 0\n13: 0\n14: 0\n15: 2\n16: 0\n17: 3\n18: 3\n19: false\n20: 1\n21: 0\n22: 1\n23: 0\n24: 0\n25: 0\n26: 5\n27: 0\n28: 3\n29: 3\n30: false\n31: false\n32: false\n33: 1\n34: 0\n35: 5\n36: 1\n37: false\n38: 1\n39: 0\n40: 5\n41: 1\n42: 1\n43: false\n44: 1\n45: 0\n46: 1\n47: 1\n48: 2\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: false\n55: false\n56: 0\n57: 0\n58: 0\n59: 0\n60: 0\n61: 3\n62: 3\n63: 0\n64: false\n65: 0\n66: 0\n67: false\n68: 0\n69: 0\n70: 3\n71: 3\n72: false\n73: false\n74: false\n75: false\n76: false",
      "ergoTreeScript": "{\n  val coll1 = CONTEXT.dataInputs\n  val bool2 = coll1.size > placeholder[Int](0)\n  val coll3 = SELF.R6[Coll[Byte]].get\n  val coll4 = SELF.R4[Coll[Byte]].get\n  val coll5 = placeholder[Coll[Byte]](1)\n  val coll6 = INPUTS.filter({(box6: Box) =>\n      val coll8 = box6.tokens\n      (coll8.size >= placeholder[Int](2)) && (coll8(placeholder[Int](3))._1 == coll3)\n    })\n  val coll7 = INPUTS.filter({(box7: Box) =>\n      val coll9 = box7.tokens\n      (coll9.size >= placeholder[Int](4)) && (coll9(placeholder[Int](5))._1 == coll3)\n    })\n  val coll8 = coll1.filter({(box8: Box) =>\n      val coll10 = box8.tokens\n      (coll10.size >= placeholder[Int](6)) && (coll10(placeholder[Int](7))._1 == coll3)\n    })\n  if (bool2) {(\n    val coll9 = coll1.filter({(box9: Box) =>\n        val coll11 = box9.tokens\n        (coll11.size >= placeholder[Int](8)) && (coll11(placeholder[Int](9))._1 == coll3)\n      })\n    if (coll9.size != placeholder[Int](10)) { sigmaProp(placeholder[Boolean](11)) } else {(\n      val box10 = coll9(placeholder[Int](12))\n      val coll11 = box10.tokens\n      sigmaProp(\n        ((coll11.size > placeholder[Int](13)) && (coll11(placeholder[Int](14))._1 == coll3)) && (box10.R4[Int].get == placeholder[Int](15))\n      ) && sigmaProp(coll4.slice(placeholder[Int](16), placeholder[Int](17)) == coll5) && proveDlog(\n        decodePoint(coll4.slice(placeholder[Int](18), coll4.size))\n      ) || sigmaProp(INPUTS.exists({(box12: Box) => box12.propositionBytes == coll4 }))\n    )}\n  )} else { sigmaProp(placeholder[Boolean](19)) } || if (bool2) {(\n    val coll9 = coll1.filter({(box9: Box) =>\n        val coll11 = box9.tokens\n        (coll11.size >= placeholder[Int](20)) && (coll11(placeholder[Int](21))._1 == coll3)\n      })\n    if (coll9.size == placeholder[Int](22)) {(\n      val box10 = coll9(placeholder[Int](23))\n      if (box10.R4[Int].get == placeholder[Int](24)) {\n        sigmaProp(HEIGHT.toLong >= box10.R8[Coll[Long]].get(placeholder[Int](25)) + placeholder[Long](26)) && sigmaProp(\n          coll4.slice(placeholder[Int](27), placeholder[Int](28)) == coll5\n        ) && proveDlog(decodePoint(coll4.slice(placeholder[Int](29), coll4.size))) || sigmaProp(\n          INPUTS.exists({(box11: Box) => box11.propositionBytes == coll4 })\n        )\n      } else { sigmaProp(placeholder[Boolean](30)) }\n    )} else { sigmaProp(placeholder[Boolean](31)) }\n  )} else { sigmaProp(placeholder[Boolean](32)) } || sigmaProp(if (coll6.size == placeholder[Int](33)) {(\n      val box9 = coll6(placeholder[Int](34))\n      (HEIGHT.toLong >= box9.R8[Coll[Long]].get(placeholder[Int](35))) && (box9.R4[Int].get == placeholder[Int](36))\n    )} else { placeholder[Boolean](37) }) || sigmaProp(if (coll7.size == placeholder[Int](38)) {(\n      val box9 = coll7(placeholder[Int](39))\n      (((HEIGHT.toLong < box9.R8[Coll[Long]].get(placeholder[Int](40))) && (SELF.R5[Coll[Byte]].get == box9.R6[(Coll[Byte], Coll[Byte])].get._2)) && (OUTPUTS.filter({(box10: Box) => box10.propositionBytes == box9.propositionBytes }).size == placeholder[Int](41))) && (box9.R4[Int].get == placeholder[Int](42))\n    )} else { placeholder[Boolean](43) }) || if (coll8.size == placeholder[Int](44)) {(\n    val box9 = coll8(placeholder[Int](45))\n    if (box9.R4[Int].get == placeholder[Int](46)) {(\n      val coll10 = SELF.propositionBytes\n      val coll11 = OUTPUTS.filter(\n        {(box11: Box) => ((box11.propositionBytes != coll10) && box11.R6[Coll[Byte]].isDefined) && (box11.R6[Coll[Byte]].get == coll3) }\n      )\n      val coll12 = box9.R9[Coll[Coll[Byte]]].get\n      val coll13 = coll12(placeholder[Int](47))\n      val coll14 = coll12(placeholder[Int](48))\n      val tuple15 = box9.R6[(Coll[Byte], Coll[Byte])].get\n      val coll16 = tuple15._2\n      if (coll11.size == placeholder[Int](49)) {(\n        val coll17 = coll11(placeholder[Int](50)).tokens.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 == coll13 })\n        sigmaProp(if (coll17.size > placeholder[Int](51)) { coll17(placeholder[Int](52))._2 } else { placeholder[Long](53) } >= INPUTS.filter({(box18: Box) =>\n              val coll20 = box18.propositionBytes\n              if ((coll20 == coll10) || (((coll20 != coll10) && box18.R6[Coll[Byte]].isDefined) && (box18.R6[Coll[Byte]].get == coll3))) {(\n                val opt21 = box18.R6[Coll[Byte]]\n                if (opt21.isDefined) { opt21.get == coll3 } else { placeholder[Boolean](54) }\n              )} else { placeholder[Boolean](55) }\n            }).fold(placeholder[Long](56), {(tuple18: (Long, Box)) =>\n              val coll20 = tuple18._2.tokens.filter({(tuple20: (Coll[Byte], Long)) => tuple20._1 == coll13 })\n              tuple18._1 + if (coll20.size > placeholder[Int](57)) { coll20(placeholder[Int](58))._2 } else { placeholder[Long](59) }\n            })) && if (coll14.slice(placeholder[Int](60), placeholder[Int](61)) == coll5) {\n          proveDlog(decodePoint(coll14.slice(placeholder[Int](62), coll14.size)))\n        } else { sigmaProp(INPUTS.exists({(box18: Box) => box18.propositionBytes == coll14 })) } || if (coll16.size > placeholder[Int](63)) {(\n          val coll18 = if (SELF.R5[Coll[Byte]].get == coll16) { coll4 } else {(\n            val coll18 = coll1.filter({(box18: Box) =>\n                val opt20 = box18.R5[Coll[Byte]]\n                if (opt20.isDefined) { opt20.get == coll16 } else { placeholder[Boolean](64) }\n              })\n            if (coll18.size > placeholder[Int](65)) {(\n              val box19 = coll18(placeholder[Int](66))\n              val coll20 = box19.R4[Coll[Byte]].get\n              if (box19.R9[Coll[Long]].get.fold(placeholder[Boolean](67), {(tuple21: (Boolean, Long)) =>\n                  val bool23 = tuple21._1\n                  if (bool23) { bool23 } else { blake2b256(box19.R7[Coll[Byte]].get.append(box9.R5[Coll[Byte]].get).append(longToByteArray(tuple21._2)).append(box19.R8[Coll[Byte]].get).append(coll20).append(tuple15._1)) == box19.R5[Coll[Byte]].get }\n                })) { coll20 } else { Coll[Byte]() }\n            )} else { Coll[Byte]() }\n          )}\n          val i19 = coll18.size\n          if (i19 > placeholder[Int](68)) {\n            if (coll18.slice(placeholder[Int](69), placeholder[Int](70)) == coll5) { proveDlog(decodePoint(coll18.slice(placeholder[Int](71), i19))) } else {\n              sigmaProp(INPUTS.exists({(box20: Box) => box20.propositionBytes == coll18 }))\n            }\n          } else { sigmaProp(placeholder[Boolean](72)) }\n        )} else { sigmaProp(placeholder[Boolean](73)) }\n      )} else { sigmaProp(placeholder[Boolean](74)) }\n    )} else { sigmaProp(placeholder[Boolean](75)) }\n  )} else { sigmaProp(placeholder[Boolean](76)) }\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
          "index": 0,
          "amount": 100,
          "name": "CAT",
          "decimals": 2,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "0e20d9925b96cebed2c0a11487f7ad0633344e9e13f4bace51b297c8bbff30da2409",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "d9925b96cebed2c0a11487f7ad0633344e9e13f4bace51b297c8bbff30da2409"
        },
        "R6": {
          "serializedValue": "0e20b09da2f796090fb0a11216b73410d2899f9c2ed7d05e3197a8268e1ba356f54d",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "b09da2f796090fb0a11216b73410d2899f9c2ed7d05e3197a8268e1ba356f54d"
        },
        "R8": {
          "serializedValue": "0e204fb6f9682dc1873413aa2c653e0d3d19de376f1ae76b47ba8b7495fd7e999589",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "4fb6f9682dc1873413aa2c653e0d3d19de376f1ae76b47ba8b7495fd7e999589"
        },
        "R7": {
          "serializedValue": "0e206770bdfc8802d3bb58cb4ff01df04896a6a5dae2f28685618be33b19bdeb578d",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "6770bdfc8802d3bb58cb4ff01df04896a6a5dae2f28685618be33b19bdeb578d"
        },
        "R9": {
          "serializedValue": "11053250044018",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[25,40,2,32,12]"
        },
        "R4": {
          "serializedValue": "0e240008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7"
        }
      }
    },
    {
      "boxId": "e47ed4343350f0f50c77be4a94d0110152d69a7d800a9e95ed4737ec0d51f9e4",
      "value": 892391640,
      "index": 2,
      "spendingProof": "b0425d9e580df25feac43304f6122891cf41a7c17867e9137193fbaf0f8bad3bd7e686f94434fe34216edae51ecf9916babfdb4fdf4b338d",
      "outputBlockId": "11ba737e4f8431dbf13dae57a3fdb62d6d5d6288c8da33f5a63ddacd61a71fa0",
      "outputTransactionId": "ed4ca685fb3bc6a6bdd4b2b2e39cc1a655dad926661c57d045640597860edb6b",
      "outputIndex": 2,
      "outputGlobalIndex": 52929352,
      "outputCreatedAt": 1698370,
      "outputSettledAt": 1698372,
      "ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
      "address": "9fcwctfPQPkDfHgxBns5Uu3dwWpaoywhkpLEobLuztfQuV5mt3T",
      "assets": [
        {
          "tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
          "index": 0,
          "amount": 95826188,
          "name": "CAT",
          "decimals": 2,
          "type": "EIP-004"
        },
        {
          "tokenId": "8d441ed68557bec21b52fb41d75e77b3fd86ad50c7cde09e7bd9871f9dd44973",
          "index": 1,
          "amount": 100,
          "name": "TEST CAT V1 APT",
          "decimals": 2,
          "type": "EIP-004"
        },
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