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Transaction

2/1/2026 05:36:10 AM
ID: a59c6a1693...c679
Inputs (5)
#0
291638cb0a8a...d523
Spent
Address:
4NhQeipASDXo...n53k
Output transaction:
290af2b47ba2...810d
Settlement height:
1,712,289
Value:
0.428852291 ERG
Tokens:
Borrow Token QUACKS - Beta-2.0
0
#1
9a7297361aff...e85a
Spent
Address:
2GHGXUgJzMYF...z4aL
Output transaction:
a2a92542bf0b...643a
Settlement height:
1,712,298
Value:
0.001 ERG
Tokens:
Loading assets...
#2
b9f55184c1a6...5ca2
Spent
Address:
2GQ3qdXbya8Q...SLLq
Output transaction:
a2a92542bf0b...643a
Settlement height:
1,712,298
Value:
0.001 ERG
Tokens:
Loading assets...
#3
1223172a8b9a...5562
Spent
Address:
9gSsDJixycev...7zSy
Output transaction:
7df004e11ea9...0610
Settlement height:
1,712,267
Value:
0.002 ERG
#4
557411b474dc...fa7a
Spent
Address:
9gSsDJixycev...7zSy
Output transaction:
4d334b5fdd52...cac4
Settlement height:
1,712,277
Value:
0.457085578 ERG
Tokens:
Loading assets...
Outputs (6)
#0
9c8d0bd5c073...b2d1
Spent
Address:
4NhQeipASDXo...n53k
Spent in transaction:
4f8a3c16f9be...f467
Settlement height:
1,712,309
Value:
0.428852291 ERG
Tokens:
Borrow Token QUACKS - Beta-2.0
0
#1
362c6059672c...973d
Spent
Address:
2GHGXUgJzMYF...z4aL
Spent in transaction:
4f8a3c16f9be...f467
Settlement height:
1,712,309
Value:
0.001 ERG
Tokens:
Loading assets...
#2
011127dda9b8...82af
Unspent
Address:
2GQ3qdXbya8Q...SLLq
Settlement height:
1,712,309
Value:
0.001 ERG
Tokens:
Loading assets...
#3
32ed6257efae...0d08
Spent
Address:
9gSsDJixycev...7zSy
Spent in transaction:
3219b8885540...3211
Settlement height:
1,712,309
Value:
0.454085578 ERG
Tokens:
Loading assets...
#4
a8767db8040b...3258
Spent
Address:
9gSsDJixycev...7zSy
Spent in transaction:
662e89ceebeb...b5ac
Settlement height:
1,712,309
Value:
0.003 ERG
#5
4a945dc3b7a1...08ba
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
ba0b7354473d...9f85
Settlement height:
1,712,309
Value:
0.002 ERG
Transaction Details
Status: Confirmed
Size: 8.53 KB
Received time: 2/1/2026 05:36:10 AM
Included in blocks: 1,712,309
Confirmations: 62,411
Total coins transferred: 0.889937869 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000229 ERG
Raw Transaction Data
{
  "id": "a59c6a16939be34144c5672e765bcd1fca4232248d416fcfa94dbd0c618fc679",
  "blockId": "9de4b6cda0c454bd8d7cf7bef9d088bcf32dbe60040f1a8d7ae07d64be58da98",
  "inclusionHeight": 1712309,
  "timestamp": 1769924170666,
  "index": 20,
  "globalIndex": 10235026,
  "numConfirmations": 62411,
  "inputs": [
    {
      "boxId": "291638cb0a8a9bc3428c3f6a80d0528d8c62fa5cf4b4906c9650687f86cbd523",
      "value": 428852291,
      "index": 0,
      "spendingProof": "d832cbd991994ed224e9fe0b7d4c4478086e46c3676df3c27a79a598764cc29199aef7907386274b934e6d197626bc7109dd5f3877b788bc",
      "outputBlockId": "8008bbfe2a9cb40459237f6bb533d6ab7001508bd19934f7a86ac29d297318ea",
      "outputTransactionId": "290af2b47ba20daa073e78008c4e3b391fa3d4be4c7aa265b5b2bb6d59b3810d",
      "outputIndex": 0,
      "outputGlobalIndex": 53317892,
      "outputCreatedAt": 1712288,
      "outputSettledAt": 1712289,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(55,-102,-19,75,93,-5,-25,19,-113,-67,83,-35,-36,10,-128,-118,-87,-96,-126,-87,-103,111,-38,-72,62,-31,47,-120,100,-54,-35,-116)\n3: 0\n4: 3\n5: 0\n6: 0\n7: 0\n8: CBigInt(10000000000000000)\n9: 0\n10: 0\n11: Coll(89,-83,113,-48,20,-42,-71,-125,108,111,56,97,72,97,123,73,-123,-65,106,-7,-24,-125,-55,14,127,-94,-110,94,17,83,103,-38)\n12: 0\n13: 1\n14: Coll(8,-103,-112,69,27,-76,48,-16,90,-123,-12,-17,59,-53,110,-65,-123,43,61,110,-26,-115,-122,-41,-122,88,-71,-52,-17,32,7,79)\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 0\n22: 32\n23: 32\n24: 40\n25: 6\n26: 1000\n27: 0\n28: 0\n29: 0\n30: 0\n31: 0\n32: 1\n33: 2\n34: 0\n35: 0\n36: 0\n37: 1\n38: 0\n39: 8\n40: 0\n41: 8\n42: 0\n43: 1\n44: 10000000\n45: 1\n46: 1000000\n47: 1000\n48: 1000\n49: 0\n50: 0\n51: 0\n52: 1000000\n53: 10000000\n54: 5\n55: 1000000\n56: 10000000\n57: 100000000\n58: 100000000\n59: 100000000\n60: 0\n61: 1\n62: 3\n63: 2\n64: 3\n65: 5\n66: 6\n67: 7\n68: 1000\n69: 1\n70: 1\n71: 980000\n72: 1000000\n73: CBigInt(1)\n74: 0\n75: 0\n76: 0\n77: 0\n78: -1\n79: 1\n80: 1\n81: 2000000\n82: 0\n83: 0\n84: 0\n85: true\n86: 0\n87: 1000000",
      "ergoTreeScript": "{\n  val coll1 = SELF.R7[Coll[Byte]].get\n  val coll2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == coll1)\n    })\n  val coll3 = SELF.propositionBytes\n  val coll4 = placeholder[Coll[Byte]](2)\n  val coll5 = INPUTS.filter({(box5: Box) => box5.propositionBytes == coll3 })\n  val i6 = coll5.indexOf(SELF, placeholder[Int](3))\n  val coll7 = SELF.R9[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](4))\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](5))\n  val coll11 = tuple10._1\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val ge13 = SELF.R5[GroupElement].get\n  val l14 = SELF.R6[Long].get\n  val coll15 = SELF.R8[Coll[Byte]].get\n  val l16 = SELF.value\n  val func17 = {(box17: Box) =>\n    val coll19 = box17.propositionBytes\n    val bool20 = coll19 == coll3\n    bool20\n  }\n  val coll18 = OUTPUTS.filter(func17)\n  val box19 = coll18.getOrElse(i6, SELF)\n  val coll20 = box19.tokens\n  val tuple21 = coll20(placeholder[Int](6))\n  val l22 = tuple21._2\n  val i23 = INPUTS.indexOf(SELF, placeholder[Int](7))\n  val bi24 = placeholder[BigInt](8)\n  val bi25 = CONTEXT.dataInputs.filter({(box25: Box) =>\n      val coll27 = box25.tokens\n      (coll27.size > placeholder[Int](9)) && (coll27(placeholder[Int](10))._1 == placeholder[Coll[Byte]](11))\n    })(placeholder[Int](12)).R5[BigInt].get\n  val l26 = tuple10._2\n  val bi27 = l26.toBigInt\n  val coll28 = coll9.slice(placeholder[Int](13), coll9.size)\n  val coll29 = placeholder[Coll[Byte]](14)\n  val func30 = {(box30: Box) =>\n    val coll32 = box30.propositionBytes\n    val coll33 = blake2b256(coll32)\n    val bool34 = coll33 == coll4\n    bool34\n  }\n  val coll31 = OUTPUTS.filter(func30)\n  val box32 = coll31.getOrElse(i23, SELF)\n  val coll33 = box32.tokens\n  val tuple34 = coll33(placeholder[Int](15))\n  val l35 = coll7(placeholder[Int](16))\n  val i36 = coll5.size\n  val bool37 = i36 == placeholder[Int](17)\n  val l38 = HEIGHT.toLong\n  val l39 = coll7(placeholder[Int](18))\n  val l40 = coll7(placeholder[Int](19))\n  val l41 = l39 + l40\n  val l42 = coll7(placeholder[Int](20))\n  val coll43 = coll15.slice(placeholder[Int](21), placeholder[Int](22))\n  val coll44 = coll15.slice(placeholder[Int](23), placeholder[Int](24))\n  val l45 = coll7(placeholder[Int](25))\n  val bi46 = bi27 * bi25 / bi24\n  val bi47 = if (l38 < l41) {(\n    val i47 = placeholder[Int](26)\n    bi46 * l45.toBigInt + i47.toBigInt / i47.toBigInt\n  )} else { bi46 }\n  val box48 = coll31.getOrElse(placeholder[Int](27), SELF)\n  val coll49 = box48.tokens\n  val tuple50 = coll49(placeholder[Int](28))\n  val func51 = {(box51: Box) =>\n    val coll53 = box51.propositionBytes\n    val coll54 = blake2b256(coll53)\n    val bool55 = coll54 == coll4\n    bool55\n  }\n  val coll52 = OUTPUTS.filter(func51)\n  val box53 = coll52.getOrElse(placeholder[Int](29), SELF)\n  val coll54 = box53.tokens\n  val tuple55 = coll54(placeholder[Int](30))\n  if (coll2.size > placeholder[Int](31)) {(\n    val func56 = func17\n    val coll57 = coll18\n    val i58 = coll57.size\n    val func59 = func30\n    val coll60 = coll31\n    val box61 = coll2.getOrElse(i6, SELF)\n    val coll62 = box61.R4[Coll[Long]].get\n    val l63 = coll62(placeholder[Int](32))\n    val l64 = coll62(placeholder[Int](33))\n    if (i58 > placeholder[Int](34)) {(\n      val box65 = box19\n      val bool66 = OUTPUTS.map({(box66: Box) => box66.id }).indexOf(box65.id, placeholder[Int](35)) == box61.R9[Coll[Int]].get(\n        placeholder[Int](36)\n      ) - placeholder[Int](37)\n      val l67 = box65.value\n      val coll68 = coll20\n      val tuple69 = tuple21\n      val coll70 = box65.R4[Coll[Byte]].get\n      val ge71 = box65.R5[GroupElement].get\n      val coll72 = box65.R7[Coll[Byte]].get\n      val bool73 = ((((l67 >= l8) && (tuple69._1 == coll11)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)\n      val coll74 = box65.R8[Coll[Byte]].get\n      val l75 = box65.R6[Long].get\n      val coll76 = box65.R9[Coll[Long]].get\n      val bool77 = coll76.slice(placeholder[Int](38), placeholder[Int](39)) == coll7.slice(placeholder[Int](40), placeholder[Int](41))\n      if (coll60.size > placeholder[Int](42)) {(\n        val bi78 = l22.toBigInt\n        val box79 = box32\n        val coll80 = coll33\n        val tuple81 = coll80(placeholder[Int](43))\n        val tuple82 = tuple34\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16)) && (l67 <= l16 + placeholder[Long](44))) && (\n                            bi78 >= bi27 - tuple81._2.toBigInt * bi24 / bi25\n                          )\n                        ) && (coll68.slice(placeholder[Int](45), coll68.size) == coll28)\n                      ) && (l75 == l14)\n                    ) && bool77\n                  ) && (((box79.value >= placeholder[Long](46)) && (tuple82._1 == coll11)) && (tuple81._1 == coll29))\n                ) && (tuple82._2 == l26 - l22)\n              ) && (l63.toBigInt >= bi78 * bi25 / bi24 * l35.toBigInt / placeholder[Int](47).toBigInt)\n            ) && bool37\n          ) && (l38 >= l41)\n        )\n      )} else {(\n        val bi78 = l63.toBigInt\n        val i79 = placeholder[Int](48)\n        val bi80 = l22.toBigInt * bi25 / bi24 * l35.toBigInt / i79.toBigInt\n        val bool81 = bi78 >= bi80\n        val prop82 = sigmaProp(INPUTS.filter({(box82: Box) =>\n              val coll84 = box82.tokens\n              ((coll84.size > placeholder[Int](49)) && (coll84(placeholder[Int](50))._1 == coll43)) && (box82.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n            }).size > placeholder[Int](51)) || proveDlog(ge13)\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](52))) && (l67 <= l16 + placeholder[Long](53))) && (\n                      coll68 == coll9\n                    )\n                  ) && (l75 > l38 + l42)\n                ) && (l75 < l38 + l42 + placeholder[Long](54))\n              ) && (bi78 < bi80)\n            ) && bool77\n          ) && bool37\n        ) || sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](55))) && (l67 <= l16 + placeholder[Long](56))) && (\n                      coll68 == coll9\n                    )\n                  ) && (l14 != placeholder[Long](57))\n                ) && (l75 == placeholder[Long](58))\n              ) && bool81\n            ) && bool77\n          ) && bool37\n        ) || prop82 && sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool73 && bool66) && (coll15 == coll74)) && (bi78 >= bi47 * l64.toBigInt / i79.toBigInt)) && (tuple69 == tuple10)) && (\n                            l75 == placeholder[Long](59)\n                          )\n                        ) && bool81\n                      ) && ((coll76(placeholder[Int](60)) == l64) && (coll76(placeholder[Int](61)) == coll62(placeholder[Int](62))))\n                    ) && (i36 == i58)\n                  ) && (coll76(placeholder[Int](63)) == l42)\n                ) && (coll76(placeholder[Int](64)) == l8)\n              ) && (coll76(placeholder[Int](65)) == l39)\n            ) && (coll76(placeholder[Int](66)) == l45)\n          ) && (coll76(placeholder[Int](67)) == l40)\n        ) || prop82 && sigmaProp(\n          ((((((bool73 && (l67 == l16)) && (coll68 == coll9)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)) && (coll76 == coll7)) && (\n            i36 == i58\n          )\n        )\n      )}\n    )} else {(\n      val bi65 = l63.toBigInt\n      val i66 = placeholder[Int](68)\n      val box67 = box48\n      val coll68 = coll49\n      val tuple69 = tuple50\n      val tuple70 = coll68(placeholder[Int](69))\n      val coll71 = SELF.id\n      val bi72 = bi65 - bi47\n      val bi73 = coll7(placeholder[Int](70)).toBigInt\n      val bi74 = bi72 * i66.toBigInt - bi73 / i66.toBigInt\n      val l75 = tuple70._2\n      sigmaProp(\n        (\n          (\n            (\n              (\n                (((bi65 <= bi47 * l35.toBigInt / i66.toBigInt) && (l38 >= l14)) || (l38 > SELF.creationInfo._1.toLong + placeholder[Long](71))) && (\n                  (((box67.value >= placeholder[Long](72)) && (tuple69._1 == coll11)) && (tuple70._1 == coll29)) && (box67.id != coll71)\n                )\n              ) && (tuple69._2 == l26)\n            ) && if (bi74 < placeholder[BigInt](73)) { l75.toBigInt >= bi65 } else {(\n              val box76 = OUTPUTS.filter({(box76: Box) => box76.propositionBytes == coll12 }).getOrElse(placeholder[Int](74), SELF)\n              val tuple77 = box76.tokens(placeholder[Int](75))\n              (((l75.toBigInt >= bi47 + bi72 * bi73 / i66.toBigInt) && (tuple77._2.toBigInt >= bi74)) && (tuple77._1 == coll29)) && (box76.id != coll71)\n            )}\n          ) && (\n            INPUTS.map({(box76: Box) => box76.id }).indexOf(coll71, placeholder[Int](76)) == box61.R9[Coll[Int]].get(placeholder[Int](77)) * placeholder[Int](\n              78\n            ) - placeholder[Int](79)\n          )\n        ) && bool37\n      )\n    )}\n  )} else {(\n    val func56 = func51\n    val coll57 = coll52\n    val box58 = box53\n    val coll59 = coll54\n    val tuple60 = tuple55\n    val tuple61 = coll59(placeholder[Int](80))\n    sigmaProp(\n      (\n        (\n          (\n            ((((box58.value >= placeholder[Long](81)) && (tuple60._1 == coll11)) && (tuple61._1 == coll29)) && (box58.id != SELF.id)) && (tuple60._2 == l26)\n          ) && (tuple61._2.toBigInt > bi47)\n        ) && if (INPUTS.filter({(box62: Box) =>\n            val coll64 = box62.tokens\n            ((coll64.size > placeholder[Int](82)) && (coll64(placeholder[Int](83))._1 == coll43)) && (box62.R9[Coll[Byte]].get == coll44)\n          }).size > placeholder[Int](84)) { placeholder[Boolean](85) } else {(\n          val box62 = OUTPUTS.filter({(box62: Box) => box62.propositionBytes == coll12 }).getOrElse(placeholder[Int](86), SELF)\n          ((box62.value >= l16 - placeholder[Long](87)) && (box62.tokens == coll28)) && (box62.id != SELF.id)\n        )}\n      ) && bool37\n    )\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "d1064b874331e51b1ed5b35a9842b2f76f7e19d85c1ad38039f7fb248bda0535",
          "index": 0,
          "amount": 4000000,
          "name": "Borrow Token QUACKS - Beta-2.0",
          "decimals": 9,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "SGroupElement",
          "renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        },
        "R6": {
          "serializedValue": "058084af5f",
          "sigmaType": "SLong",
          "renderedValue": "100000000"
        },
        "R8": {
          "serializedValue": "0e2802517063d1264324a9455d6a3e577eaa9715dcae71123fb3f32c0d37662cfe0e019c0d58ae5102b8",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "02517063d1264324a9455d6a3e577eaa9715dcae71123fb3f32c0d37662cfe0e019c0d58ae5102b8"
        },
        "R7": {
          "serializedValue": "0e201c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "1c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59"
        },
        "R9": {
          "serializedValue": "110890163c108087a70e00d6ebd001641e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1416,30,8,15000000,0,1710827,50,15]"
        },
        "R4": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        }
      }
    },
    {
      "boxId": "9a7297361aff31d06e2f11c4f9bd412c8279ccd5814ba23caa942bbd63a2e85a",
      "value": 1000000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "d539c494e46601dddc8e9204f756ea9e277fc925ff44ce8509fd89a155d4292b",
      "outputTransactionId": "a2a92542bf0be16432f16828bbf19460cf39b0797bf11d9d671a0783c079643a",
      "outputIndex": 1,
      "outputGlobalIndex": 53318283,
      "outputCreatedAt": 1712293,
      "outputSettledAt": 1712298,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "1c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT QUACKS - Beta-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "1a012046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1]"
        },
        "R6": {
          "serializedValue": "1101f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400]"
        },
        "R8": {
          "serializedValue": "1a00",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[]"
        },
        "R7": {
          "serializedValue": "1100",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[]"
        },
        "R9": {
          "serializedValue": "10020202",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[1,1]"
        },
        "R4": {
          "serializedValue": "110a80a0b787e905eabecc1990163c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,26841013,1416,30,15000000,8,0,50,15,20000000]"
        }
      }
    },
    {
      "boxId": "b9f55184c1a697703a9a15cca70abd494d2a14ba2a8446ab1b825fe164845ca2",
      "value": 1000000,
      "index": 2,
      "spendingProof": "7f72fd8a3e526736d1caa768984c70e5dfded4ebf725fd51e5abcbd6ca62998a543980e75ba8f270a869d4e4d8503f981018d440e63bc8c6",
      "outputBlockId": "d539c494e46601dddc8e9204f756ea9e277fc925ff44ce8509fd89a155d4292b",
      "outputTransactionId": "a2a92542bf0be16432f16828bbf19460cf39b0797bf11d9d671a0783c079643a",
      "outputIndex": 2,
      "outputGlobalIndex": 53318284,
      "outputCreatedAt": 1712293,
      "outputSettledAt": 1712298,
      "ergoTree": "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",
      "ergoTreeConstants": "0: Coll(62,-107,41,96,-84,30,-81,-48,107,19,-38,-11,-85,-104,12,26,109,40,32,-51,92,53,-123,-19,-58,-109,-66,-3,11,58,71,76)\n1: 0\n2: 2\n3: 1\n4: 0\n5: 0\n6: 32\n7: 32\n8: 40\n9: 2\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 2\n16: 0\n17: 0\n18: 1\n19: 0\n20: 2\n21: 2\n22: 0\n23: 0\n24: 100\n25: 10\n26: 5000000\n27: 5000000\n28: 5000000\n29: 0\n30: 0\n31: 0\n32: 0\n33: 0\n34: true\n35: 1\n36: 0\n37: 0\n38: 1000000\n39: false\n40: false\n41: false",
      "ergoTreeScript": "{\n  val ge1 = SELF.R7[GroupElement].get\n  val coll2 = placeholder[Coll[Byte]](0)\n  val coll3 = INPUTS.filter({(box3: Box) => blake2b256(box3.propositionBytes) == coll2 })\n  val tuple4 = SELF.tokens(placeholder[Int](1))\n  val coll5 = tuple4._1\n  val coll6 = SELF.R9[Coll[Coll[Byte]]].get\n  proveDlog(ge1) || sigmaProp(if (coll3.size == placeholder[Int](2)) {(\n      val box7 = coll3(placeholder[Int](3))\n      val box8 = coll3(placeholder[Int](4))\n      if (coll3.forall({(box9: Box) =>\n          val coll11 = box9.R8[Coll[Byte]].get\n          (coll11.slice(placeholder[Int](5), placeholder[Int](6)) == coll5) && coll6.exists({(coll12: Coll[Byte]) => coll12 == coll11.slice(placeholder[Int](7), placeholder[Int](8)) })\n        })) {(\n        val i9 = placeholder[Int](9) * INPUTS.indexOf(box7, placeholder[Int](10))\n        val i10 = i9 + placeholder[Int](11)\n        if (OUTPUTS.size > i10) {(\n          val l11 = OUTPUTS(i9 + placeholder[Int](12)).R4[Coll[Long]].get(placeholder[Int](13))\n          val l12 = OUTPUTS(i10).R4[Coll[Long]].get(placeholder[Int](14))\n          val box13 = OUTPUTS(placeholder[Int](15) * INPUTS.indexOf(box8, placeholder[Int](16)))\n          val box14 = OUTPUTS(i9)\n          val bool15 = l11 >= l12\n          val bool16 = if (bool15) { placeholder[Int](17) } else { placeholder[Int](18) } == placeholder[Int](19)\n          val box17 = if (bool16) { box13 } else { box14 }\n          val l18 = box17.value\n          val box19 = if (bool16) { box8 } else { box7 }\n          val l20 = box19.value\n          val l21 = if (bool15) { l11 - l12 } else { l12 - l11 }\n          val l22 = if (bool15) { placeholder[Long](20) * l11 } else { placeholder[Long](21) * l12 }\n          val l23 = l20 * l21 / l22\n          val l24 = l20 - l23\n          val box25 = if (bool16) { box14 } else { box13 }\n          val box26 = if (bool16) { box7 } else { box8 }\n          val l27 = box26.value + l23\n          val coll28 = box17.tokens\n          val coll29 = box19.tokens\n          val coll30 = OUTPUTS.filter({(box30: Box) => ((box30.propositionBytes == SELF.propositionBytes) && (box30.tokens.size > placeholder[Int](22))) && (box30.tokens(placeholder[Int](23))._1 == coll5) })\n          ((((if (l11 > l12) { l11 - l12 } else { l12 - l11 } * placeholder[Long](24) > placeholder[Long](25) * if (l11 < l12) { l11 } else { l12 }) && ((blake2b256(box13.propositionBytes) == coll2) && (blake2b256(box14.propositionBytes) == coll2))) && (box13.value + box14.value >= box8.value + box7.value - placeholder[Long](26))) && ((((((l18 >= l24 - placeholder[Long](27)) && (l18 <= l24)) && (box25.value >= l27)) && (box25.value <= l27 + placeholder[Long](28))) && ((coll28(placeholder[Int](29)) == coll29(placeholder[Int](30))) && (box25.tokens(placeholder[Int](31)) == box26.tokens(placeholder[Int](32))))) && coll29.indices.forall({(i31: Int) => if (i31 == placeholder[Int](33)) { placeholder[Boolean](34) } else {(\n                    val tuple33 = coll28(i31)\n                    val tuple34 = coll29(i31)\n                    val coll35 = tuple34._1\n                    val l36 = tuple34._2\n                    val l37 = l36 * l21 / l22\n                    (((tuple33._1 == coll35) && (tuple33._2 == l36 - l37)) && (box25.tokens(i31)._1 == coll35)) && (box25.tokens(i31)._2 == box26.tokens(i31)._2 + l37)\n                  )} }))) && ((coll30.size == placeholder[Int](35)) && \n              val box31 = coll30(placeholder[Int](36))\n              ((((((box31.tokens(placeholder[Int](37)) == tuple4) && (box31.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box31.R5[Coll[Coll[Byte]]].get == SELF.R5[Coll[Coll[Byte]]].get)) && (box31.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get)) && (box31.R7[GroupElement].get == ge1)) && (box31.R9[Coll[Coll[Byte]]].get == coll6)) && (box31.value >= placeholder[Long](38))\n            )\n        )} else { placeholder[Boolean](39) }\n      )} else { placeholder[Boolean](40) }\n    )} else { placeholder[Boolean](41) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "24ab4bcd206d4661c87f7e7af6cb811ce53ae54d926c58ee200d0528314d2702",
          "index": 0,
          "amount": 1000000,
          "name": null,
          "decimals": null,
          "type": null
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "1a0108019c13f7e08b0153",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019c13f7e08b0153]"
        },
        "R6": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        },
        "R8": {
          "serializedValue": "1a0108019c13f7e08b0153",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019c13f7e08b0153]"
        },
        "R7": {
          "serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "SGroupElement",
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      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(55,-102,-19,75,93,-5,-25,19,-113,-67,83,-35,-36,10,-128,-118,-87,-96,-126,-87,-103,111,-38,-72,62,-31,47,-120,100,-54,-35,-116)\n3: 0\n4: 3\n5: 0\n6: 0\n7: 0\n8: CBigInt(10000000000000000)\n9: 0\n10: 0\n11: Coll(89,-83,113,-48,20,-42,-71,-125,108,111,56,97,72,97,123,73,-123,-65,106,-7,-24,-125,-55,14,127,-94,-110,94,17,83,103,-38)\n12: 0\n13: 1\n14: Coll(8,-103,-112,69,27,-76,48,-16,90,-123,-12,-17,59,-53,110,-65,-123,43,61,110,-26,-115,-122,-41,-122,88,-71,-52,-17,32,7,79)\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 0\n22: 32\n23: 32\n24: 40\n25: 6\n26: 1000\n27: 0\n28: 0\n29: 0\n30: 0\n31: 0\n32: 1\n33: 2\n34: 0\n35: 0\n36: 0\n37: 1\n38: 0\n39: 8\n40: 0\n41: 8\n42: 0\n43: 1\n44: 10000000\n45: 1\n46: 1000000\n47: 1000\n48: 1000\n49: 0\n50: 0\n51: 0\n52: 1000000\n53: 10000000\n54: 5\n55: 1000000\n56: 10000000\n57: 100000000\n58: 100000000\n59: 100000000\n60: 0\n61: 1\n62: 3\n63: 2\n64: 3\n65: 5\n66: 6\n67: 7\n68: 1000\n69: 1\n70: 1\n71: 980000\n72: 1000000\n73: CBigInt(1)\n74: 0\n75: 0\n76: 0\n77: 0\n78: -1\n79: 1\n80: 1\n81: 2000000\n82: 0\n83: 0\n84: 0\n85: true\n86: 0\n87: 1000000",
      "ergoTreeScript": "{\n  val coll1 = SELF.R7[Coll[Byte]].get\n  val coll2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == coll1)\n    })\n  val coll3 = SELF.propositionBytes\n  val coll4 = placeholder[Coll[Byte]](2)\n  val coll5 = INPUTS.filter({(box5: Box) => box5.propositionBytes == coll3 })\n  val i6 = coll5.indexOf(SELF, placeholder[Int](3))\n  val coll7 = SELF.R9[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](4))\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](5))\n  val coll11 = tuple10._1\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val ge13 = SELF.R5[GroupElement].get\n  val l14 = SELF.R6[Long].get\n  val coll15 = SELF.R8[Coll[Byte]].get\n  val l16 = SELF.value\n  val func17 = {(box17: Box) =>\n    val coll19 = box17.propositionBytes\n    val bool20 = coll19 == coll3\n    bool20\n  }\n  val coll18 = OUTPUTS.filter(func17)\n  val box19 = coll18.getOrElse(i6, SELF)\n  val coll20 = box19.tokens\n  val tuple21 = coll20(placeholder[Int](6))\n  val l22 = tuple21._2\n  val i23 = INPUTS.indexOf(SELF, placeholder[Int](7))\n  val bi24 = placeholder[BigInt](8)\n  val bi25 = CONTEXT.dataInputs.filter({(box25: Box) =>\n      val coll27 = box25.tokens\n      (coll27.size > placeholder[Int](9)) && (coll27(placeholder[Int](10))._1 == placeholder[Coll[Byte]](11))\n    })(placeholder[Int](12)).R5[BigInt].get\n  val l26 = tuple10._2\n  val bi27 = l26.toBigInt\n  val coll28 = coll9.slice(placeholder[Int](13), coll9.size)\n  val coll29 = placeholder[Coll[Byte]](14)\n  val func30 = {(box30: Box) =>\n    val coll32 = box30.propositionBytes\n    val coll33 = blake2b256(coll32)\n    val bool34 = coll33 == coll4\n    bool34\n  }\n  val coll31 = OUTPUTS.filter(func30)\n  val box32 = coll31.getOrElse(i23, SELF)\n  val coll33 = box32.tokens\n  val tuple34 = coll33(placeholder[Int](15))\n  val l35 = coll7(placeholder[Int](16))\n  val i36 = coll5.size\n  val bool37 = i36 == placeholder[Int](17)\n  val l38 = HEIGHT.toLong\n  val l39 = coll7(placeholder[Int](18))\n  val l40 = coll7(placeholder[Int](19))\n  val l41 = l39 + l40\n  val l42 = coll7(placeholder[Int](20))\n  val coll43 = coll15.slice(placeholder[Int](21), placeholder[Int](22))\n  val coll44 = coll15.slice(placeholder[Int](23), placeholder[Int](24))\n  val l45 = coll7(placeholder[Int](25))\n  val bi46 = bi27 * bi25 / bi24\n  val bi47 = if (l38 < l41) {(\n    val i47 = placeholder[Int](26)\n    bi46 * l45.toBigInt + i47.toBigInt / i47.toBigInt\n  )} else { bi46 }\n  val box48 = coll31.getOrElse(placeholder[Int](27), SELF)\n  val coll49 = box48.tokens\n  val tuple50 = coll49(placeholder[Int](28))\n  val func51 = {(box51: Box) =>\n    val coll53 = box51.propositionBytes\n    val coll54 = blake2b256(coll53)\n    val bool55 = coll54 == coll4\n    bool55\n  }\n  val coll52 = OUTPUTS.filter(func51)\n  val box53 = coll52.getOrElse(placeholder[Int](29), SELF)\n  val coll54 = box53.tokens\n  val tuple55 = coll54(placeholder[Int](30))\n  if (coll2.size > placeholder[Int](31)) {(\n    val func56 = func17\n    val coll57 = coll18\n    val i58 = coll57.size\n    val func59 = func30\n    val coll60 = coll31\n    val box61 = coll2.getOrElse(i6, SELF)\n    val coll62 = box61.R4[Coll[Long]].get\n    val l63 = coll62(placeholder[Int](32))\n    val l64 = coll62(placeholder[Int](33))\n    if (i58 > placeholder[Int](34)) {(\n      val box65 = box19\n      val bool66 = OUTPUTS.map({(box66: Box) => box66.id }).indexOf(box65.id, placeholder[Int](35)) == box61.R9[Coll[Int]].get(\n        placeholder[Int](36)\n      ) - placeholder[Int](37)\n      val l67 = box65.value\n      val coll68 = coll20\n      val tuple69 = tuple21\n      val coll70 = box65.R4[Coll[Byte]].get\n      val ge71 = box65.R5[GroupElement].get\n      val coll72 = box65.R7[Coll[Byte]].get\n      val bool73 = ((((l67 >= l8) && (tuple69._1 == coll11)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)\n      val coll74 = box65.R8[Coll[Byte]].get\n      val l75 = box65.R6[Long].get\n      val coll76 = box65.R9[Coll[Long]].get\n      val bool77 = coll76.slice(placeholder[Int](38), placeholder[Int](39)) == coll7.slice(placeholder[Int](40), placeholder[Int](41))\n      if (coll60.size > placeholder[Int](42)) {(\n        val bi78 = l22.toBigInt\n        val box79 = box32\n        val coll80 = coll33\n        val tuple81 = coll80(placeholder[Int](43))\n        val tuple82 = tuple34\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16)) && (l67 <= l16 + placeholder[Long](44))) && (\n                            bi78 >= bi27 - tuple81._2.toBigInt * bi24 / bi25\n                          )\n                        ) && (coll68.slice(placeholder[Int](45), coll68.size) == coll28)\n                      ) && (l75 == l14)\n                    ) && bool77\n                  ) && (((box79.value >= placeholder[Long](46)) && (tuple82._1 == coll11)) && (tuple81._1 == coll29))\n                ) && (tuple82._2 == l26 - l22)\n              ) && (l63.toBigInt >= bi78 * bi25 / bi24 * l35.toBigInt / placeholder[Int](47).toBigInt)\n            ) && bool37\n          ) && (l38 >= l41)\n        )\n      )} else {(\n        val bi78 = l63.toBigInt\n        val i79 = placeholder[Int](48)\n        val bi80 = l22.toBigInt * bi25 / bi24 * l35.toBigInt / i79.toBigInt\n        val bool81 = bi78 >= bi80\n        val prop82 = sigmaProp(INPUTS.filter({(box82: Box) =>\n              val coll84 = box82.tokens\n              ((coll84.size > placeholder[Int](49)) && (coll84(placeholder[Int](50))._1 == coll43)) && (box82.R9[Coll[Coll[Byte]]].get(i23) == coll44)\n            }).size > placeholder[Int](51)) || proveDlog(ge13)\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](52))) && (l67 <= l16 + placeholder[Long](53))) && (\n                      coll68 == coll9\n                    )\n                  ) && (l75 > l38 + l42)\n                ) && (l75 < l38 + l42 + placeholder[Long](54))\n              ) && (bi78 < bi80)\n            ) && bool77\n          ) && bool37\n        ) || sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool73 && bool66) && (coll15 == coll74)) && (l67 >= l16 - placeholder[Long](55))) && (l67 <= l16 + placeholder[Long](56))) && (\n                      coll68 == coll9\n                    )\n                  ) && (l14 != placeholder[Long](57))\n                ) && (l75 == placeholder[Long](58))\n              ) && bool81\n            ) && bool77\n          ) && bool37\n        ) || prop82 && sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool73 && bool66) && (coll15 == coll74)) && (bi78 >= bi47 * l64.toBigInt / i79.toBigInt)) && (tuple69 == tuple10)) && (\n                            l75 == placeholder[Long](59)\n                          )\n                        ) && bool81\n                      ) && ((coll76(placeholder[Int](60)) == l64) && (coll76(placeholder[Int](61)) == coll62(placeholder[Int](62))))\n                    ) && (i36 == i58)\n                  ) && (coll76(placeholder[Int](63)) == l42)\n                ) && (coll76(placeholder[Int](64)) == l8)\n              ) && (coll76(placeholder[Int](65)) == l39)\n            ) && (coll76(placeholder[Int](66)) == l45)\n          ) && (coll76(placeholder[Int](67)) == l40)\n        ) || prop82 && sigmaProp(\n          ((((((bool73 && (l67 == l16)) && (coll68 == coll9)) && (coll70 == coll12)) && (ge71 == ge13)) && (coll72 == coll1)) && (coll76 == coll7)) && (\n            i36 == i58\n          )\n        )\n      )}\n    )} else {(\n      val bi65 = l63.toBigInt\n      val i66 = placeholder[Int](68)\n      val box67 = box48\n      val coll68 = coll49\n      val tuple69 = tuple50\n      val tuple70 = coll68(placeholder[Int](69))\n      val coll71 = SELF.id\n      val bi72 = bi65 - bi47\n      val bi73 = coll7(placeholder[Int](70)).toBigInt\n      val bi74 = bi72 * i66.toBigInt - bi73 / i66.toBigInt\n      val l75 = tuple70._2\n      sigmaProp(\n        (\n          (\n            (\n              (\n                (((bi65 <= bi47 * l35.toBigInt / i66.toBigInt) && (l38 >= l14)) || (l38 > SELF.creationInfo._1.toLong + placeholder[Long](71))) && (\n                  (((box67.value >= placeholder[Long](72)) && (tuple69._1 == coll11)) && (tuple70._1 == coll29)) && (box67.id != coll71)\n                )\n              ) && (tuple69._2 == l26)\n            ) && if (bi74 < placeholder[BigInt](73)) { l75.toBigInt >= bi65 } else {(\n              val box76 = OUTPUTS.filter({(box76: Box) => box76.propositionBytes == coll12 }).getOrElse(placeholder[Int](74), SELF)\n              val tuple77 = box76.tokens(placeholder[Int](75))\n              (((l75.toBigInt >= bi47 + bi72 * bi73 / i66.toBigInt) && (tuple77._2.toBigInt >= bi74)) && (tuple77._1 == coll29)) && (box76.id != coll71)\n            )}\n          ) && (\n            INPUTS.map({(box76: Box) => box76.id }).indexOf(coll71, placeholder[Int](76)) == box61.R9[Coll[Int]].get(placeholder[Int](77)) * placeholder[Int](\n              78\n            ) - placeholder[Int](79)\n          )\n        ) && bool37\n      )\n    )}\n  )} else {(\n    val func56 = func51\n    val coll57 = coll52\n    val box58 = box53\n    val coll59 = coll54\n    val tuple60 = tuple55\n    val tuple61 = coll59(placeholder[Int](80))\n    sigmaProp(\n      (\n        (\n          (\n            ((((box58.value >= placeholder[Long](81)) && (tuple60._1 == coll11)) && (tuple61._1 == coll29)) && (box58.id != SELF.id)) && (tuple60._2 == l26)\n          ) && (tuple61._2.toBigInt > bi47)\n        ) && if (INPUTS.filter({(box62: Box) =>\n            val coll64 = box62.tokens\n            ((coll64.size > placeholder[Int](82)) && (coll64(placeholder[Int](83))._1 == coll43)) && (box62.R9[Coll[Byte]].get == coll44)\n          }).size > placeholder[Int](84)) { placeholder[Boolean](85) } else {(\n          val box62 = OUTPUTS.filter({(box62: Box) => box62.propositionBytes == coll12 }).getOrElse(placeholder[Int](86), SELF)\n          ((box62.value >= l16 - placeholder[Long](87)) && (box62.tokens == coll28)) && (box62.id != SELF.id)\n        )}\n      ) && bool37\n    )\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "d1064b874331e51b1ed5b35a9842b2f76f7e19d85c1ad38039f7fb248bda0535",
          "index": 0,
          "amount": 4000000,
          "name": "Borrow Token QUACKS - Beta-2.0",
          "decimals": 9,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "SGroupElement",
          "renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        },
        "R6": {
          "serializedValue": "058084af5f",
          "sigmaType": "SLong",
          "renderedValue": "100000000"
        },
        "R8": {
          "serializedValue": "0e2824ab4bcd206d4661c87f7e7af6cb811ce53ae54d926c58ee200d0528314d2702019c0d58ae5102b8",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "24ab4bcd206d4661c87f7e7af6cb811ce53ae54d926c58ee200d0528314d2702019c0d58ae5102b8"
        },
        "R7": {
          "serializedValue": "0e201c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "1c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59"
        },
        "R9": {
          "serializedValue": "110890163c108087a70e00d6ebd001641e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1416,30,8,15000000,0,1710827,50,15]"
        },
        "R4": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        }
      },
      "spentTransactionId": "4f8a3c16f9be049f71c148e51cbea6a20acf55cb4c67a5cbf9e871a5e302f467",
      "mainChain": true
    },
    {
      "boxId": "362c6059672caea27704f19eb3c34106275ea8b50c7c8533f39e1603cf47973d",
      "transactionId": "a59c6a16939be34144c5672e765bcd1fca4232248d416fcfa94dbd0c618fc679",
      "blockId": "9de4b6cda0c454bd8d7cf7bef9d088bcf32dbe60040f1a8d7ae07d64be58da98",
      "value": 1000000,
      "index": 1,
      "globalIndex": 53318537,
      "creationHeight": 1712308,
      "settlementHeight": 1712309,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "1c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT QUACKS - Beta-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "1a012046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1]"
        },
        "R6": {
          "serializedValue": "1101f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400]"
        },
        "R8": {
          "serializedValue": "1a00",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[]"
        },
        "R7": {
          "serializedValue": "1100",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[]"
        },
        "R9": {
          "serializedValue": "10020202",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[1,1]"
        },
        "R4": {
          "serializedValue": "110a80a0b787e905d6f7b61990163c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,26664427,1416,30,15000000,8,0,50,15,20000000]"
        }
      },
      "spentTransactionId": "4f8a3c16f9be049f71c148e51cbea6a20acf55cb4c67a5cbf9e871a5e302f467",
      "mainChain": true
    },
    {
      "boxId": "011127dda9b85cf782854b077ea4f86f05c40c8b0a9ba04d93e34355bd6f82af",
      "transactionId": "a59c6a16939be34144c5672e765bcd1fca4232248d416fcfa94dbd0c618fc679",
      "blockId": "9de4b6cda0c454bd8d7cf7bef9d088bcf32dbe60040f1a8d7ae07d64be58da98",
      "value": 1000000,
      "index": 2,
      "globalIndex": 53318538,
      "creationHeight": 1712308,
      "settlementHeight": 1712309,
      "ergoTree": "19e9062a0e203e952960ac1eafd06b13daf5ab980c1a6d2820cd5c3585edc693befd0b3a474c0400040404020400040004400440045004040400040604040402040204040400040004020400050405040400040005c80105140580ade2040580ade2040580ade2040400040004000400040001010402040004000580897a010001000100d806d601e4c6a70707d6027300d603b5a4d901036393cbc272037202d604b2db6308a7730100d6058c720401d606e4c6a7091aeb02cd7201d19593b172037302d802d607b27203730300d608b2720373040095af7203d9010963d801d60be4c67209080eed93b4720b730573067205ae7206d9010c0e93720cb4720b73077308d802d6099c7309dc0c1aa4027207730ad60a9a7209730b9591b1a5720ad814d60bb2e4c6b2a59a7209730c000411730d00d60cb2e4c6b2a5720a000411730e00d60db2a59c730fdc0c1aa4027208731000d60eb2a5720900d60f92720b720cd6109395720f731173127313d611957210720d720ed612c17211d61395721072087207d614c17213d61595720f99720b720c99720c720bd61695720f9c7314720b9c7315720cd6179d9c721472157216d6189972147217d619957210720e720dd61a95721072077208d61b9ac1721a7217d61cdb63087211d61ddb63087213d61eb5a5d9011e63eded93c2721ec2a791b1db6308721e7316938cb2db6308721e731700017205edededed919c9591720b720c99720b720c99720c720b73189c7319958f720b720c720b720ced93cbc2720d720293cbc2720e7202929ac1720dc1720e999ac17208c17207731aededededed927212997218731b907212721892c17219721b90c172199a721b731ced93b2721c731d00b2721d731e0093b2db63087219731f00b2db6308721a732000afdb0c0e721dd9011f049593721f73217322d805d621b2721c721f00d622b2721d721f00d6238c722201d6248c722202d6259d9c722472157216ededed938c7221017223938c7221029972247225938cb2db63087219721f00017223938cb2db63087219721f00029a8cb2db6308721a721f00027225ed93b1721e7323d801d61fb2721e732400edededededed93b2db6308721f732500720493e4c6721f040ee4c6a7040e93e4c6721f051ae4c6a7051a93e4c6721f060ee4c6a7060e93e4c6721f0707720193e4c6721f091a720692c1721f7326732773287329",
      "ergoTreeConstants": "0: Coll(62,-107,41,96,-84,30,-81,-48,107,19,-38,-11,-85,-104,12,26,109,40,32,-51,92,53,-123,-19,-58,-109,-66,-3,11,58,71,76)\n1: 0\n2: 2\n3: 1\n4: 0\n5: 0\n6: 32\n7: 32\n8: 40\n9: 2\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 2\n16: 0\n17: 0\n18: 1\n19: 0\n20: 2\n21: 2\n22: 0\n23: 0\n24: 100\n25: 10\n26: 5000000\n27: 5000000\n28: 5000000\n29: 0\n30: 0\n31: 0\n32: 0\n33: 0\n34: true\n35: 1\n36: 0\n37: 0\n38: 1000000\n39: false\n40: false\n41: false",
      "ergoTreeScript": "{\n  val ge1 = SELF.R7[GroupElement].get\n  val coll2 = placeholder[Coll[Byte]](0)\n  val coll3 = INPUTS.filter({(box3: Box) => blake2b256(box3.propositionBytes) == coll2 })\n  val tuple4 = SELF.tokens(placeholder[Int](1))\n  val coll5 = tuple4._1\n  val coll6 = SELF.R9[Coll[Coll[Byte]]].get\n  proveDlog(ge1) || sigmaProp(if (coll3.size == placeholder[Int](2)) {(\n      val box7 = coll3(placeholder[Int](3))\n      val box8 = coll3(placeholder[Int](4))\n      if (coll3.forall({(box9: Box) =>\n          val coll11 = box9.R8[Coll[Byte]].get\n          (coll11.slice(placeholder[Int](5), placeholder[Int](6)) == coll5) && coll6.exists({(coll12: Coll[Byte]) => coll12 == coll11.slice(placeholder[Int](7), placeholder[Int](8)) })\n        })) {(\n        val i9 = placeholder[Int](9) * INPUTS.indexOf(box7, placeholder[Int](10))\n        val i10 = i9 + placeholder[Int](11)\n        if (OUTPUTS.size > i10) {(\n          val l11 = OUTPUTS(i9 + placeholder[Int](12)).R4[Coll[Long]].get(placeholder[Int](13))\n          val l12 = OUTPUTS(i10).R4[Coll[Long]].get(placeholder[Int](14))\n          val box13 = OUTPUTS(placeholder[Int](15) * INPUTS.indexOf(box8, placeholder[Int](16)))\n          val box14 = OUTPUTS(i9)\n          val bool15 = l11 >= l12\n          val bool16 = if (bool15) { placeholder[Int](17) } else { placeholder[Int](18) } == placeholder[Int](19)\n          val box17 = if (bool16) { box13 } else { box14 }\n          val l18 = box17.value\n          val box19 = if (bool16) { box8 } else { box7 }\n          val l20 = box19.value\n          val l21 = if (bool15) { l11 - l12 } else { l12 - l11 }\n          val l22 = if (bool15) { placeholder[Long](20) * l11 } else { placeholder[Long](21) * l12 }\n          val l23 = l20 * l21 / l22\n          val l24 = l20 - l23\n          val box25 = if (bool16) { box14 } else { box13 }\n          val box26 = if (bool16) { box7 } else { box8 }\n          val l27 = box26.value + l23\n          val coll28 = box17.tokens\n          val coll29 = box19.tokens\n          val coll30 = OUTPUTS.filter({(box30: Box) => ((box30.propositionBytes == SELF.propositionBytes) && (box30.tokens.size > placeholder[Int](22))) && (box30.tokens(placeholder[Int](23))._1 == coll5) })\n          ((((if (l11 > l12) { l11 - l12 } else { l12 - l11 } * placeholder[Long](24) > placeholder[Long](25) * if (l11 < l12) { l11 } else { l12 }) && ((blake2b256(box13.propositionBytes) == coll2) && (blake2b256(box14.propositionBytes) == coll2))) && (box13.value + box14.value >= box8.value + box7.value - placeholder[Long](26))) && ((((((l18 >= l24 - placeholder[Long](27)) && (l18 <= l24)) && (box25.value >= l27)) && (box25.value <= l27 + placeholder[Long](28))) && ((coll28(placeholder[Int](29)) == coll29(placeholder[Int](30))) && (box25.tokens(placeholder[Int](31)) == box26.tokens(placeholder[Int](32))))) && coll29.indices.forall({(i31: Int) => if (i31 == placeholder[Int](33)) { placeholder[Boolean](34) } else {(\n                    val tuple33 = coll28(i31)\n                    val tuple34 = coll29(i31)\n                    val coll35 = tuple34._1\n                    val l36 = tuple34._2\n                    val l37 = l36 * l21 / l22\n                    (((tuple33._1 == coll35) && (tuple33._2 == l36 - l37)) && (box25.tokens(i31)._1 == coll35)) && (box25.tokens(i31)._2 == box26.tokens(i31)._2 + l37)\n                  )} }))) && ((coll30.size == placeholder[Int](35)) && \n              val box31 = coll30(placeholder[Int](36))\n              ((((((box31.tokens(placeholder[Int](37)) == tuple4) && (box31.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box31.R5[Coll[Coll[Byte]]].get == SELF.R5[Coll[Coll[Byte]]].get)) && (box31.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get)) && (box31.R7[GroupElement].get == ge1)) && (box31.R9[Coll[Coll[Byte]]].get == coll6)) && (box31.value >= placeholder[Long](38))\n            )\n        )} else { placeholder[Boolean](39) }\n      )} else { placeholder[Boolean](40) }\n    )} else { placeholder[Boolean](41) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "24ab4bcd206d4661c87f7e7af6cb811ce53ae54d926c58ee200d0528314d2702",
          "index": 0,
          "amount": 1000000,
          "name": null,
          "decimals": null,
          "type": null
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "1a0208019c13f7e08b015308019c0d58ae5102b8",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019c13f7e08b0153,019c0d58ae5102b8]"
        },
        "R6": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        },
        "R8": {
          "serializedValue": "1a0208019c13f7e08b015308019c0d58ae5102b8",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019c13f7e08b0153,019c0d58ae5102b8]"
        },
        "R7": {
          "serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "SGroupElement",
          "renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        },
        "R9": {
          "serializedValue": "1a0208019c13f7e08b015308019c0d58ae5102b8",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019c13f7e08b0153,019c0d58ae5102b8]"
        },
        "R4": {
          "serializedValue": "0e2024ab4bcd206d4661c87f7e7af6cb811ce53ae54d926c58ee200d0528314d2702",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "24ab4bcd206d4661c87f7e7af6cb811ce53ae54d926c58ee200d0528314d2702"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "32ed6257efae904726debc5819d896d06af85a0400a567081d72e7c183ad0d08",
      "transactionId": "a59c6a16939be34144c5672e765bcd1fca4232248d416fcfa94dbd0c618fc679",
      "blockId": "9de4b6cda0c454bd8d7cf7bef9d088bcf32dbe60040f1a8d7ae07d64be58da98",
      "value": 454085578,
      "index": 3,
      "globalIndex": 53318539,
      "creationHeight": 1712308,
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