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Transaction

1/25/2026 07:09:24 AM
ID: 037f9b8d1d...7de4
Inputs (6)
#0
5f980289c83b...e16a
Spent
Address:
LBLbAU1k4cGz...hYN5
Output transaction:
42f00b66b115...6aa1
Settlement height:
1,707,319
Value:
0.403 ERG
Tokens:
Borrow Token QUACKS - Beta-2.0
0
#1
9a61a18f23fc...8f02
Spent
Address:
2GHGXUgJzMYF...z4aL
Output transaction:
42f00b66b115...6aa1
Settlement height:
1,707,319
Value:
0.001 ERG
Tokens:
Loading assets...
#2
863245c9862c...83be
Spent
Address:
iGoXksJG9JWy...Ykjv
Output transaction:
e9f53e321575...f321
Settlement height:
1,707,316
Value:
0.001 ERG
Tokens:
Loading assets...
#3
10fff07ef97f...ee25
Spent
Address:
9gSsDJixycev...7zSy
Output transaction:
570e475f81ca...8242
Settlement height:
1,707,243
Value:
0.0072 ERG
Tokens:
Loading assets...
#4
ea4b18e752c5...dfa1
Spent
Address:
9gSsDJixycev...7zSy
Output transaction:
aa96a07d1460...242c
Settlement height:
1,707,249
Value:
0.001 ERG
Tokens:
QUACKS
4
#5
2e51e4bca421...d69f
Spent
Address:
9gSsDJixycev...7zSy
Output transaction:
e9f53e321575...f321
Settlement height:
1,707,316
Value:
170.18 ERG
Tokens:
Loading assets...
Outputs (7)
#0
659d036b1fc2...ef9e
Spent
Address:
LBLbAU1k4cGz...hYN5
Spent in transaction:
30329d1a86bf...1073
Settlement height:
1,707,323
Value:
0.403 ERG
Tokens:
Borrow Token QUACKS - Beta-2.0
0
#1
95fd3c6cacde...e694
Unspent
Address:
2GHGXUgJzMYF...z4aL
Settlement height:
1,707,323
Value:
0.001 ERG
Tokens:
Loading assets...
#2
f18a12d43b2d...b4ad
Unspent
Address:
iGoXksJG9JWy...Ykjv
Settlement height:
1,707,323
Value:
0.001 ERG
Tokens:
Loading assets...
#3
8bb6416c8334...6745
Spent
Address:
9gSsDJixycev...7zSy
Spent in transaction:
252462d67b7c...f0ad
Settlement height:
1,707,323
Value:
170.17 ERG
Tokens:
Loading assets...
#4
7b97c740ecf2...a2f8
Spent
Address:
9gSsDJixycev...7zSy
Spent in transaction:
f7745c124b10...5079
Settlement height:
1,707,323
Value:
0.0072 ERG
Tokens:
Loading assets...
#5
00252cdef494...0ebe
Spent
Address:
9gSsDJixycev...7zSy
Spent in transaction:
f7745c124b10...5079
Settlement height:
1,707,323
Value:
0.003 ERG
#6
8b28db88bc00...6c0e
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
8702c7e0f8d2...fb68
Settlement height:
1,707,323
Value:
0.002 ERG
Transaction Details
Status: Confirmed
Size: 8.79 KB
Received time: 1/25/2026 07:09:24 AM
Included in blocks: 1,707,323
Confirmations: 65,879
Total coins transferred: 170.59 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000222 ERG
Raw Transaction Data
{
  "id": "037f9b8d1de611a25f133ddf4af787c18bcca687fa02e62888cdad5301f27de4",
  "blockId": "09919adf423890dad9c4a5dccc76f0fa44017be8786ec5c1bb58ee4c8d08daa4",
  "inclusionHeight": 1707323,
  "timestamp": 1769324964314,
  "index": 4,
  "globalIndex": 10196852,
  "numConfirmations": 65879,
  "inputs": [
    {
      "boxId": "5f980289c83be9cf4b1570af13c78b28aabb363cb1be6e7a99bc56296596e16a",
      "value": 403000000,
      "index": 0,
      "spendingProof": "c9a53e1f29f1a52415474f19d3345625e2aa0f9c74ca8177b17de5d24a91424ada85f3e75c656e8909df5a44bcf78cb5a6c3d760ebc1036e",
      "outputBlockId": "2f184d2c0457cd7b98cc03a06a94c903a1879c52cb67ae58fc480df6015471b9",
      "outputTransactionId": "42f00b66b115b9e0c51b1e342274238335edd47fe3b91f758951e835ce6d6aa1",
      "outputIndex": 1,
      "outputGlobalIndex": 53172858,
      "outputCreatedAt": 1707317,
      "outputSettledAt": 1707319,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-71,-15,98,-120,-119,37,-9,-89,9,-103,24,-50,-69,-115,32,-115,-120,92,-95,66,126,-83,97,43,-94,-102,50,32,-54,87,40,72)\n3: 0\n4: 0\n5: 0\n6: CBigInt(10000000000000000)\n7: 0\n8: 0\n9: Coll(-128,-82,71,2,-93,-122,50,-91,-59,119,86,30,127,72,88,111,-66,-16,126,-75,63,-79,90,70,41,-2,-65,27,23,-36,-20,66)\n10: 0\n11: 1\n12: 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)\n13: 0\n14: 0\n15: 1\n16: 5\n17: 7\n18: 2\n19: 0\n20: 32\n21: 32\n22: 40\n23: 1000\n24: 6\n25: 0\n26: 0\n27: 0\n28: 0\n29: 0\n30: 1\n31: 0\n32: 0\n33: 0\n34: 1\n35: 3\n36: 0\n37: 8\n38: 0\n39: 8\n40: 0\n41: 1\n42: 10000000\n43: 1\n44: 1000000\n45: 1000\n46: 1000\n47: 0\n48: 0\n49: 0\n50: 1000000\n51: 10000000\n52: 5\n53: 1000000\n54: 10000000\n55: 100000000\n56: 100000000\n57: 1000\n58: 1\n59: 1\n60: 980000\n61: 1000000\n62: CBigInt(1)\n63: 0\n64: 0\n65: 0\n66: 0\n67: -1\n68: 1\n69: 1\n70: 2000000\n71: 0\n72: 0\n73: 0\n74: true\n75: 0\n76: 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 i5 = INPUTS.indexOf(SELF, placeholder[Int](3))\n  val coll6 = SELF.R9[Coll[Long]].get\n  val coll7 = SELF.tokens\n  val tuple8 = coll7(placeholder[Int](4))\n  val coll9 = tuple8._1\n  val coll10 = SELF.R4[Coll[Byte]].get\n  val ge11 = SELF.R5[GroupElement].get\n  val l12 = SELF.R6[Long].get\n  val coll13 = SELF.R8[Coll[Byte]].get\n  val l14 = SELF.value\n  val func15 = {(box15: Box) =>\n    val coll17 = box15.propositionBytes\n    val bool18 = coll17 == coll3\n    bool18\n  }\n  val coll16 = OUTPUTS.filter(func15)\n  val box17 = coll16.getOrElse(i5, SELF)\n  val coll18 = box17.tokens\n  val tuple19 = coll18(placeholder[Int](5))\n  val l20 = tuple19._2\n  val bi21 = placeholder[BigInt](6)\n  val bi22 = CONTEXT.dataInputs.filter({(box22: Box) =>\n      val coll24 = box22.tokens\n      (coll24.size > placeholder[Int](7)) && (coll24(placeholder[Int](8))._1 == placeholder[Coll[Byte]](9))\n    })(placeholder[Int](10)).R5[BigInt].get\n  val l23 = tuple8._2\n  val bi24 = l23.toBigInt\n  val coll25 = coll7.slice(placeholder[Int](11), coll7.size)\n  val coll26 = placeholder[Coll[Byte]](12)\n  val func27 = {(box27: Box) =>\n    val coll29 = box27.propositionBytes\n    val coll30 = blake2b256(coll29)\n    val bool31 = coll30 == coll4\n    bool31\n  }\n  val coll28 = OUTPUTS.filter(func27)\n  val box29 = coll28.getOrElse(i5, SELF)\n  val coll30 = box29.tokens\n  val tuple31 = coll30(placeholder[Int](13))\n  val l32 = coll6(placeholder[Int](14))\n  val i33 = INPUTS.filter({(box33: Box) => box33.propositionBytes == coll3 }).size\n  val bool34 = i33 == placeholder[Int](15)\n  val l35 = HEIGHT.toLong\n  val l36 = coll6(placeholder[Int](16)) + coll6(placeholder[Int](17))\n  val l37 = coll6(placeholder[Int](18))\n  val coll38 = coll13.slice(placeholder[Int](19), placeholder[Int](20))\n  val coll39 = coll13.slice(placeholder[Int](21), placeholder[Int](22))\n  val bi40 = bi24 * bi22 / bi21\n  val bi41 = if (l35 < l36) {(\n    val i41 = placeholder[Int](23)\n    bi40 * coll6(placeholder[Int](24)).toBigInt + i41.toBigInt / i41.toBigInt\n  )} else { bi40 }\n  val box42 = coll28.getOrElse(placeholder[Int](25), SELF)\n  val coll43 = box42.tokens\n  val tuple44 = coll43(placeholder[Int](26))\n  val func45 = {(box45: Box) =>\n    val coll47 = box45.propositionBytes\n    val coll48 = blake2b256(coll47)\n    val bool49 = coll48 == coll4\n    bool49\n  }\n  val coll46 = OUTPUTS.filter(func45)\n  val box47 = coll46.getOrElse(placeholder[Int](27), SELF)\n  val coll48 = box47.tokens\n  val tuple49 = coll48(placeholder[Int](28))\n  if (coll2.size > placeholder[Int](29)) {(\n    val func50 = func15\n    val coll51 = coll16\n    val i52 = coll51.size\n    val func53 = func27\n    val coll54 = coll28\n    val box55 = coll2.getOrElse(i5, SELF)\n    val l56 = box55.R4[Coll[Long]].get(placeholder[Int](30))\n    if (i52 > placeholder[Int](31)) {(\n      val box57 = box17\n      val bool58 = OUTPUTS.map({(box58: Box) => box58.id }).indexOf(box57.id, placeholder[Int](32)) == box55.R9[Coll[Int]].get(\n        placeholder[Int](33)\n      ) - placeholder[Int](34)\n      val l59 = box57.value\n      val coll60 = coll18\n      val tuple61 = tuple19\n      val coll62 = box57.R4[Coll[Byte]].get\n      val ge63 = box57.R5[GroupElement].get\n      val coll64 = box57.R7[Coll[Byte]].get\n      val bool65 = ((((l59 >= coll6(placeholder[Int](35))) && (tuple61._1 == coll9)) && (coll62 == coll10)) && (ge63 == ge11)) && (coll64 == coll1)\n      val coll66 = box57.R8[Coll[Byte]].get\n      val l67 = box57.R6[Long].get\n      val coll68 = box57.R9[Coll[Long]].get\n      val bool69 = coll68.slice(placeholder[Int](36), placeholder[Int](37)) == coll6.slice(placeholder[Int](38), placeholder[Int](39))\n      if (coll54.size > placeholder[Int](40)) {(\n        val bi70 = l20.toBigInt\n        val box71 = box29\n        val coll72 = coll30\n        val tuple73 = coll72(placeholder[Int](41))\n        val tuple74 = tuple31\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool65 && bool58) && (coll13 == coll66)) && (l59 >= l14)) && (l59 <= l14 + placeholder[Long](42))) && (\n                            bi70 >= bi24 - tuple73._2.toBigInt * bi21 / bi22\n                          )\n                        ) && (coll60.slice(placeholder[Int](43), coll60.size) == coll25)\n                      ) && (l67 == l12)\n                    ) && bool69\n                  ) && (((box71.value >= placeholder[Long](44)) && (tuple74._1 == coll9)) && (tuple73._1 == coll26))\n                ) && (tuple74._2 == l23 - l20)\n              ) && (l56.toBigInt >= bi70 * bi22 / bi21 * l32.toBigInt / placeholder[Int](45).toBigInt)\n            ) && bool34\n          ) && (l35 >= l36)\n        )\n      )} else {(\n        val bi70 = l56.toBigInt\n        val bi71 = l20.toBigInt * bi22 / bi21 * l32.toBigInt / placeholder[Int](46).toBigInt\n        val prop72 = sigmaProp(INPUTS.filter({(box72: Box) =>\n              val coll74 = box72.tokens\n              ((coll74.size > placeholder[Int](47)) && (coll74(placeholder[Int](48))._1 == coll38)) && (box72.R9[Coll[Coll[Byte]]].get(i5) == coll39)\n            }).size > placeholder[Int](49)) || proveDlog(ge11)\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool65 && bool58) && (coll13 == coll66)) && (l59 >= l14 - placeholder[Long](50))) && (l59 <= l14 + placeholder[Long](51))) && (\n                      coll60 == coll7\n                    )\n                  ) && (l67 > l35 + l37)\n                ) && (l67 < l35 + l37 + placeholder[Long](52))\n              ) && (bi70 < bi71)\n            ) && bool69\n          ) && bool34\n        ) || sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool65 && bool58) && (coll13 == coll66)) && (l59 >= l14 - placeholder[Long](53))) && (l59 <= l14 + placeholder[Long](54))) && (\n                      coll60 == coll7\n                    )\n                  ) && (l12 != placeholder[Long](55))\n                ) && (l67 == placeholder[Long](56))\n              ) && (bi70 >= bi71)\n            ) && bool69\n          ) && bool34\n        ) || prop72 && sigmaProp(l59 != l14) || prop72 && sigmaProp(\n          ((((((bool65 && (l59 == l14)) && (coll60 == coll7)) && (coll62 == coll10)) && (ge63 == ge11)) && (coll64 == coll1)) && (coll68 == coll6)) && (\n            i33 == i52\n          )\n        )\n      )}\n    )} else {(\n      val bi57 = l56.toBigInt\n      val i58 = placeholder[Int](57)\n      val box59 = box42\n      val coll60 = coll43\n      val tuple61 = tuple44\n      val tuple62 = coll60(placeholder[Int](58))\n      val coll63 = SELF.id\n      val bi64 = bi57 - bi41\n      val bi65 = coll6(placeholder[Int](59)).toBigInt\n      val bi66 = bi64 * i58.toBigInt - bi65 / i58.toBigInt\n      val l67 = tuple62._2\n      sigmaProp(\n        (\n          (\n            (\n              (\n                (((bi57 <= bi41 * l32.toBigInt / i58.toBigInt) && (l35 >= l12)) || (l35 > SELF.creationInfo._1.toLong + placeholder[Long](60))) && (\n                  (((box59.value >= placeholder[Long](61)) && (tuple61._1 == coll9)) && (tuple62._1 == coll26)) && (box59.id != coll63)\n                )\n              ) && (tuple61._2 == l23)\n            ) && if (bi66 < placeholder[BigInt](62)) { l67.toBigInt >= bi57 } else {(\n              val box68 = OUTPUTS.filter({(box68: Box) => box68.propositionBytes == coll10 }).getOrElse(placeholder[Int](63), SELF)\n              val tuple69 = box68.tokens(placeholder[Int](64))\n              (((l67.toBigInt >= bi41 + bi64 * bi65 / i58.toBigInt) && (tuple69._2.toBigInt >= bi66)) && (tuple69._1 == coll26)) && (box68.id != coll63)\n            )}\n          ) && (\n            INPUTS.map({(box68: Box) => box68.id }).indexOf(coll63, placeholder[Int](65)) == box55.R9[Coll[Int]].get(placeholder[Int](66)) * placeholder[Int](\n              67\n            ) - placeholder[Int](68)\n          )\n        ) && bool34\n      )\n    )}\n  )} else {(\n    val func50 = func45\n    val coll51 = coll46\n    val box52 = box47\n    val coll53 = coll48\n    val tuple54 = tuple49\n    val tuple55 = coll53(placeholder[Int](69))\n    sigmaProp(\n      (\n        (\n          (((((box52.value >= placeholder[Long](70)) && (tuple54._1 == coll9)) && (tuple55._1 == coll26)) && (box52.id != SELF.id)) && (tuple54._2 == l23)) && (\n            tuple55._2.toBigInt > bi41\n          )\n        ) && if (INPUTS.filter({(box56: Box) =>\n            val coll58 = box56.tokens\n            ((coll58.size > placeholder[Int](71)) && (coll58(placeholder[Int](72))._1 == coll38)) && (box56.R9[Coll[Byte]].get == coll39)\n          }).size > placeholder[Int](73)) { placeholder[Boolean](74) } else {(\n          val box56 = OUTPUTS.filter({(box56: Box) => box56.propositionBytes == coll10 }).getOrElse(placeholder[Int](75), SELF)\n          ((box56.value >= l14 - placeholder[Long](76)) && (box56.tokens == coll25)) && (box56.id != SELF.id)\n        )}\n      ) && bool34\n    )\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "4f25cd397bc58acc0d63d582f72bfcbf90665206508826937945cb7976a0e029",
          "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": "0e0100",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "00"
        },
        "R7": {
          "serializedValue": "0e20ad05f5ed620bdc28e3cccbeb579d0b4cb818cd6fc2d00c3cd57ee5c3b43e2a0c",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "ad05f5ed620bdc28e3cccbeb579d0b4cb818cd6fc2d00c3cd57ee5c3b43e2a0c"
        },
        "R9": {
          "serializedValue": "110892163c108087a70e00f4b4d001641e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1417,30,8,15000000,0,1707322,50,15]"
        },
        "R4": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        }
      }
    },
    {
      "boxId": "9a61a18f23fc0b42e02571416e11d211fcb216844f7e3633934da7aebcce8f02",
      "value": 1000000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "2f184d2c0457cd7b98cc03a06a94c903a1879c52cb67ae58fc480df6015471b9",
      "outputTransactionId": "42f00b66b115b9e0c51b1e342274238335edd47fe3b91f758951e835ce6d6aa1",
      "outputIndex": 3,
      "outputGlobalIndex": 53172860,
      "outputCreatedAt": 1707317,
      "outputSettledAt": 1707319,
      "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": "ad05f5ed620bdc28e3cccbeb579d0b4cb818cd6fc2d00c3cd57ee5c3b43e2a0c",
          "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": "10020404",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[2,2]"
        },
        "R4": {
          "serializedValue": "110a80a0b787e905b8a8ea1792163c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,24988188,1417,30,15000000,8,0,50,15,20000000]"
        }
      }
    },
    {
      "boxId": "863245c9862ca6cb922102b05a6c33ab5a8d46cd132c20251a0c62ef25e883be",
      "value": 1000000,
      "index": 2,
      "spendingProof": "26d7f393f916d6f386e466b36de229d584a913f93fb6ae8a9bfb451575907e21dd17acf1dc3e7df5ea8d5c896774ee05279cbe6f6db7d1dd982f57c1fc287bbbbce068c28132967f257f150f127dcbf25b9004916162ddb63c58e01abac1c1a1c52a1a38085971408d3d45d2b70b98bc",
      "outputBlockId": "cab27137968b3277e2db78844d8a2d23539290eb4346c634df6162f333a6d748",
      "outputTransactionId": "e9f53e3215750a08b048b2f40b99aa14e2b038267ebddbc2008ca3568a08f321",
      "outputIndex": 2,
      "outputGlobalIndex": 53172781,
      "outputCreatedAt": 1707311,
      "outputSettledAt": 1707316,
      "ergoTree": "100308cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c708cd03199bd9865508d9e9c998e828d8313cb1bf83d43ac79c467d33f8d1223fde382c04ff02eb027300ea027301d191a37302",
      "ergoTreeConstants": "0: SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))\n1: SigmaProp(ProveDlog(ECPoint(199bd9,a14ea8,...)))\n2: -192",
      "ergoTreeScript": "{placeholder[SigmaProp](0) || placeholder[SigmaProp](1) && sigmaProp(HEIGHT > placeholder[Int](2))}",
      "address": "iGoXksJG9JWyoXeiwQXkZBYp9RT3WHWkxKAhTHA3CwnXorkurV1pNbPJNUVfHjT9uwYeRhz7mP84xjZt1yruCqNs8uAdN8M7F6oBxtsKppsKhxtjXRien5CjWyYkjv",
      "assets": [
        {
          "tokenId": "85238717b43a3614f81a586729f2530b67d07661be5aa8fca85d64e4f4a28172",
          "index": 0,
          "amount": 1000000,
          "name": null,
          "decimals": null,
          "type": null
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "1a0108019bf3ea21c43a54",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019bf3ea21c43a54]"
        },
        "R6": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        },
        "R8": {
          "serializedValue": "1a0108019bf3ea21c43a54",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019bf3ea21c43a54]"
        },
        "R7": {
          "serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "SGroupElement",
          "renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        },
        "R9": {
          "serializedValue": "1a0108019bf3ea21c43a54",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019bf3ea21c43a54]"
        },
        "R4": {
          "serializedValue": "0e2085238717b43a3614f81a586729f2530b67d07661be5aa8fca85d64e4f4a28172",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "85238717b43a3614f81a586729f2530b67d07661be5aa8fca85d64e4f4a28172"
        }
      }
    },
    {
      "boxId": "10fff07ef97f83e0c72195bd29b680f2d51d842d9c46e0553313e46f137aee25",
      "value": 7200000,
      "index": 3,
      "spendingProof": "f45d703b060f5426c13bb209dd05beedb6f1daadbefeaa43eeb6de7989c0ffb622d25fc14fed08e902b1e289032cc87d1f2dc785ea41ac94",
      "outputBlockId": "681af376f9cb9789b1d408877502bb339fa781cfe070156391b10594583e12d4",
      "outputTransactionId": "570e475f81cabd0d8b628591dc920b5cefe7142b3a9e9b4eb4a0350356798242",
      "outputIndex": 2,
      "outputGlobalIndex": 53170817,
      "outputCreatedAt": 1707239,
      "outputSettledAt": 1707243,
      "ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
      "address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
      "assets": [
        {
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          "index": 0,
          "amount": 87553,
          "name": "Lend Token SigRSV-0e",
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          "type": "EIP-004"
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          "name": "junk",
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          "type": "EIP-004"
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          "type": "EIP-004"
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        {
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        {
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        {
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        {
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          "type": "EIP-004"
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        {
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        {
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        {
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        },
        {
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        },
        {
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        },
        {
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        },
        {
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        {
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        },
        {
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        {
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        {
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          "type": "EIP-004"
        },
        {
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      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-71,-15,98,-120,-119,37,-9,-89,9,-103,24,-50,-69,-115,32,-115,-120,92,-95,66,126,-83,97,43,-94,-102,50,32,-54,87,40,72)\n3: 0\n4: 0\n5: 0\n6: CBigInt(10000000000000000)\n7: 0\n8: 0\n9: Coll(-128,-82,71,2,-93,-122,50,-91,-59,119,86,30,127,72,88,111,-66,-16,126,-75,63,-79,90,70,41,-2,-65,27,23,-36,-20,66)\n10: 0\n11: 1\n12: 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)\n13: 0\n14: 0\n15: 1\n16: 5\n17: 7\n18: 2\n19: 0\n20: 32\n21: 32\n22: 40\n23: 1000\n24: 6\n25: 0\n26: 0\n27: 0\n28: 0\n29: 0\n30: 1\n31: 0\n32: 0\n33: 0\n34: 1\n35: 3\n36: 0\n37: 8\n38: 0\n39: 8\n40: 0\n41: 1\n42: 10000000\n43: 1\n44: 1000000\n45: 1000\n46: 1000\n47: 0\n48: 0\n49: 0\n50: 1000000\n51: 10000000\n52: 5\n53: 1000000\n54: 10000000\n55: 100000000\n56: 100000000\n57: 1000\n58: 1\n59: 1\n60: 980000\n61: 1000000\n62: CBigInt(1)\n63: 0\n64: 0\n65: 0\n66: 0\n67: -1\n68: 1\n69: 1\n70: 2000000\n71: 0\n72: 0\n73: 0\n74: true\n75: 0\n76: 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 i5 = INPUTS.indexOf(SELF, placeholder[Int](3))\n  val coll6 = SELF.R9[Coll[Long]].get\n  val coll7 = SELF.tokens\n  val tuple8 = coll7(placeholder[Int](4))\n  val coll9 = tuple8._1\n  val coll10 = SELF.R4[Coll[Byte]].get\n  val ge11 = SELF.R5[GroupElement].get\n  val l12 = SELF.R6[Long].get\n  val coll13 = SELF.R8[Coll[Byte]].get\n  val l14 = SELF.value\n  val func15 = {(box15: Box) =>\n    val coll17 = box15.propositionBytes\n    val bool18 = coll17 == coll3\n    bool18\n  }\n  val coll16 = OUTPUTS.filter(func15)\n  val box17 = coll16.getOrElse(i5, SELF)\n  val coll18 = box17.tokens\n  val tuple19 = coll18(placeholder[Int](5))\n  val l20 = tuple19._2\n  val bi21 = placeholder[BigInt](6)\n  val bi22 = CONTEXT.dataInputs.filter({(box22: Box) =>\n      val coll24 = box22.tokens\n      (coll24.size > placeholder[Int](7)) && (coll24(placeholder[Int](8))._1 == placeholder[Coll[Byte]](9))\n    })(placeholder[Int](10)).R5[BigInt].get\n  val l23 = tuple8._2\n  val bi24 = l23.toBigInt\n  val coll25 = coll7.slice(placeholder[Int](11), coll7.size)\n  val coll26 = placeholder[Coll[Byte]](12)\n  val func27 = {(box27: Box) =>\n    val coll29 = box27.propositionBytes\n    val coll30 = blake2b256(coll29)\n    val bool31 = coll30 == coll4\n    bool31\n  }\n  val coll28 = OUTPUTS.filter(func27)\n  val box29 = coll28.getOrElse(i5, SELF)\n  val coll30 = box29.tokens\n  val tuple31 = coll30(placeholder[Int](13))\n  val l32 = coll6(placeholder[Int](14))\n  val i33 = INPUTS.filter({(box33: Box) => box33.propositionBytes == coll3 }).size\n  val bool34 = i33 == placeholder[Int](15)\n  val l35 = HEIGHT.toLong\n  val l36 = coll6(placeholder[Int](16)) + coll6(placeholder[Int](17))\n  val l37 = coll6(placeholder[Int](18))\n  val coll38 = coll13.slice(placeholder[Int](19), placeholder[Int](20))\n  val coll39 = coll13.slice(placeholder[Int](21), placeholder[Int](22))\n  val bi40 = bi24 * bi22 / bi21\n  val bi41 = if (l35 < l36) {(\n    val i41 = placeholder[Int](23)\n    bi40 * coll6(placeholder[Int](24)).toBigInt + i41.toBigInt / i41.toBigInt\n  )} else { bi40 }\n  val box42 = coll28.getOrElse(placeholder[Int](25), SELF)\n  val coll43 = box42.tokens\n  val tuple44 = coll43(placeholder[Int](26))\n  val func45 = {(box45: Box) =>\n    val coll47 = box45.propositionBytes\n    val coll48 = blake2b256(coll47)\n    val bool49 = coll48 == coll4\n    bool49\n  }\n  val coll46 = OUTPUTS.filter(func45)\n  val box47 = coll46.getOrElse(placeholder[Int](27), SELF)\n  val coll48 = box47.tokens\n  val tuple49 = coll48(placeholder[Int](28))\n  if (coll2.size > placeholder[Int](29)) {(\n    val func50 = func15\n    val coll51 = coll16\n    val i52 = coll51.size\n    val func53 = func27\n    val coll54 = coll28\n    val box55 = coll2.getOrElse(i5, SELF)\n    val l56 = box55.R4[Coll[Long]].get(placeholder[Int](30))\n    if (i52 > placeholder[Int](31)) {(\n      val box57 = box17\n      val bool58 = OUTPUTS.map({(box58: Box) => box58.id }).indexOf(box57.id, placeholder[Int](32)) == box55.R9[Coll[Int]].get(\n        placeholder[Int](33)\n      ) - placeholder[Int](34)\n      val l59 = box57.value\n      val coll60 = coll18\n      val tuple61 = tuple19\n      val coll62 = box57.R4[Coll[Byte]].get\n      val ge63 = box57.R5[GroupElement].get\n      val coll64 = box57.R7[Coll[Byte]].get\n      val bool65 = ((((l59 >= coll6(placeholder[Int](35))) && (tuple61._1 == coll9)) && (coll62 == coll10)) && (ge63 == ge11)) && (coll64 == coll1)\n      val coll66 = box57.R8[Coll[Byte]].get\n      val l67 = box57.R6[Long].get\n      val coll68 = box57.R9[Coll[Long]].get\n      val bool69 = coll68.slice(placeholder[Int](36), placeholder[Int](37)) == coll6.slice(placeholder[Int](38), placeholder[Int](39))\n      if (coll54.size > placeholder[Int](40)) {(\n        val bi70 = l20.toBigInt\n        val box71 = box29\n        val coll72 = coll30\n        val tuple73 = coll72(placeholder[Int](41))\n        val tuple74 = tuple31\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          ((((bool65 && bool58) && (coll13 == coll66)) && (l59 >= l14)) && (l59 <= l14 + placeholder[Long](42))) && (\n                            bi70 >= bi24 - tuple73._2.toBigInt * bi21 / bi22\n                          )\n                        ) && (coll60.slice(placeholder[Int](43), coll60.size) == coll25)\n                      ) && (l67 == l12)\n                    ) && bool69\n                  ) && (((box71.value >= placeholder[Long](44)) && (tuple74._1 == coll9)) && (tuple73._1 == coll26))\n                ) && (tuple74._2 == l23 - l20)\n              ) && (l56.toBigInt >= bi70 * bi22 / bi21 * l32.toBigInt / placeholder[Int](45).toBigInt)\n            ) && bool34\n          ) && (l35 >= l36)\n        )\n      )} else {(\n        val bi70 = l56.toBigInt\n        val bi71 = l20.toBigInt * bi22 / bi21 * l32.toBigInt / placeholder[Int](46).toBigInt\n        val prop72 = sigmaProp(INPUTS.filter({(box72: Box) =>\n              val coll74 = box72.tokens\n              ((coll74.size > placeholder[Int](47)) && (coll74(placeholder[Int](48))._1 == coll38)) && (box72.R9[Coll[Coll[Byte]]].get(i5) == coll39)\n            }).size > placeholder[Int](49)) || proveDlog(ge11)\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool65 && bool58) && (coll13 == coll66)) && (l59 >= l14 - placeholder[Long](50))) && (l59 <= l14 + placeholder[Long](51))) && (\n                      coll60 == coll7\n                    )\n                  ) && (l67 > l35 + l37)\n                ) && (l67 < l35 + l37 + placeholder[Long](52))\n              ) && (bi70 < bi71)\n            ) && bool69\n          ) && bool34\n        ) || sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    ((((bool65 && bool58) && (coll13 == coll66)) && (l59 >= l14 - placeholder[Long](53))) && (l59 <= l14 + placeholder[Long](54))) && (\n                      coll60 == coll7\n                    )\n                  ) && (l12 != placeholder[Long](55))\n                ) && (l67 == placeholder[Long](56))\n              ) && (bi70 >= bi71)\n            ) && bool69\n          ) && bool34\n        ) || prop72 && sigmaProp(l59 != l14) || prop72 && sigmaProp(\n          ((((((bool65 && (l59 == l14)) && (coll60 == coll7)) && (coll62 == coll10)) && (ge63 == ge11)) && (coll64 == coll1)) && (coll68 == coll6)) && (\n            i33 == i52\n          )\n        )\n      )}\n    )} else {(\n      val bi57 = l56.toBigInt\n      val i58 = placeholder[Int](57)\n      val box59 = box42\n      val coll60 = coll43\n      val tuple61 = tuple44\n      val tuple62 = coll60(placeholder[Int](58))\n      val coll63 = SELF.id\n      val bi64 = bi57 - bi41\n      val bi65 = coll6(placeholder[Int](59)).toBigInt\n      val bi66 = bi64 * i58.toBigInt - bi65 / i58.toBigInt\n      val l67 = tuple62._2\n      sigmaProp(\n        (\n          (\n            (\n              (\n                (((bi57 <= bi41 * l32.toBigInt / i58.toBigInt) && (l35 >= l12)) || (l35 > SELF.creationInfo._1.toLong + placeholder[Long](60))) && (\n                  (((box59.value >= placeholder[Long](61)) && (tuple61._1 == coll9)) && (tuple62._1 == coll26)) && (box59.id != coll63)\n                )\n              ) && (tuple61._2 == l23)\n            ) && if (bi66 < placeholder[BigInt](62)) { l67.toBigInt >= bi57 } else {(\n              val box68 = OUTPUTS.filter({(box68: Box) => box68.propositionBytes == coll10 }).getOrElse(placeholder[Int](63), SELF)\n              val tuple69 = box68.tokens(placeholder[Int](64))\n              (((l67.toBigInt >= bi41 + bi64 * bi65 / i58.toBigInt) && (tuple69._2.toBigInt >= bi66)) && (tuple69._1 == coll26)) && (box68.id != coll63)\n            )}\n          ) && (\n            INPUTS.map({(box68: Box) => box68.id }).indexOf(coll63, placeholder[Int](65)) == box55.R9[Coll[Int]].get(placeholder[Int](66)) * placeholder[Int](\n              67\n            ) - placeholder[Int](68)\n          )\n        ) && bool34\n      )\n    )}\n  )} else {(\n    val func50 = func45\n    val coll51 = coll46\n    val box52 = box47\n    val coll53 = coll48\n    val tuple54 = tuple49\n    val tuple55 = coll53(placeholder[Int](69))\n    sigmaProp(\n      (\n        (\n          (((((box52.value >= placeholder[Long](70)) && (tuple54._1 == coll9)) && (tuple55._1 == coll26)) && (box52.id != SELF.id)) && (tuple54._2 == l23)) && (\n            tuple55._2.toBigInt > bi41\n          )\n        ) && if (INPUTS.filter({(box56: Box) =>\n            val coll58 = box56.tokens\n            ((coll58.size > placeholder[Int](71)) && (coll58(placeholder[Int](72))._1 == coll38)) && (box56.R9[Coll[Byte]].get == coll39)\n          }).size > placeholder[Int](73)) { placeholder[Boolean](74) } else {(\n          val box56 = OUTPUTS.filter({(box56: Box) => box56.propositionBytes == coll10 }).getOrElse(placeholder[Int](75), SELF)\n          ((box56.value >= l14 - placeholder[Long](76)) && (box56.tokens == coll25)) && (box56.id != SELF.id)\n        )}\n      ) && bool34\n    )\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "4f25cd397bc58acc0d63d582f72bfcbf90665206508826937945cb7976a0e029",
          "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": "0e2885238717b43a3614f81a586729f2530b67d07661be5aa8fca85d64e4f4a28172019bf3fbb7e9d069",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "85238717b43a3614f81a586729f2530b67d07661be5aa8fca85d64e4f4a28172019bf3fbb7e9d069"
        },
        "R7": {
          "serializedValue": "0e20ad05f5ed620bdc28e3cccbeb579d0b4cb818cd6fc2d00c3cd57ee5c3b43e2a0c",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "ad05f5ed620bdc28e3cccbeb579d0b4cb818cd6fc2d00c3cd57ee5c3b43e2a0c"
        },
        "R9": {
          "serializedValue": "110892163c108087a70e00f4b4d001641e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1417,30,8,15000000,0,1707322,50,15]"
        },
        "R4": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        }
      },
      "spentTransactionId": "30329d1a86bf17a9563faa7817f7deb843980ac53d671d4686dac98aaf8a1073",
      "mainChain": true
    },
    {
      "boxId": "95fd3c6cacdec9a7a6466e69871c7fc4044e8ac17e518d06e6c84b43cdc3e694",
      "transactionId": "037f9b8d1de611a25f133ddf4af787c18bcca687fa02e62888cdad5301f27de4",
      "blockId": "09919adf423890dad9c4a5dccc76f0fa44017be8786ec5c1bb58ee4c8d08daa4",
      "value": 1000000,
      "index": 1,
      "globalIndex": 53172944,
      "creationHeight": 1707322,
      "settlementHeight": 1707323,
      "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": "ad05f5ed620bdc28e3cccbeb579d0b4cb818cd6fc2d00c3cd57ee5c3b43e2a0c",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT QUACKS - Beta-2.0",
          "decimals": 0,
          "type": "EIP-004"
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      ],
      "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": "110a80a0b787e905b8a8ea1792163c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,24988188,1417,30,15000000,8,0,50,15,20000000]"
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      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "f18a12d43b2d5008adeb3e0eb0572f95d5727fd9a7145929a8d3c79f7e50b4ad",
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      "value": 1000000,
      "index": 2,
      "globalIndex": 53172945,
      "creationHeight": 1707322,
      "settlementHeight": 1707323,
      "ergoTree": "100308cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c708cd03199bd9865508d9e9c998e828d8313cb1bf83d43ac79c467d33f8d1223fde382c04ff02eb027300ea027301d191a37302",
      "ergoTreeConstants": "0: SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))\n1: SigmaProp(ProveDlog(ECPoint(199bd9,a14ea8,...)))\n2: -192",
      "ergoTreeScript": "{placeholder[SigmaProp](0) || placeholder[SigmaProp](1) && sigmaProp(HEIGHT > placeholder[Int](2))}",
      "address": "iGoXksJG9JWyoXeiwQXkZBYp9RT3WHWkxKAhTHA3CwnXorkurV1pNbPJNUVfHjT9uwYeRhz7mP84xjZt1yruCqNs8uAdN8M7F6oBxtsKppsKhxtjXRien5CjWyYkjv",
      "assets": [
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          "index": 0,
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          "name": null,
          "decimals": null,
          "type": null
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      "additionalRegisters": {
        "R5": {
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          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019bf3ea21c43a54,019bf3fbb7e9d069]"
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        "R6": {
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          "sigmaType": "Coll[SByte]",
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        "R8": {
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          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019bf3ea21c43a54,019bf3fbb7e9d069]"
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        "R7": {
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          "sigmaType": "SGroupElement",
          "renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
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        "R9": {
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          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[019bf3ea21c43a54,019bf3fbb7e9d069]"
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        "R4": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "85238717b43a3614f81a586729f2530b67d07661be5aa8fca85d64e4f4a28172"
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      "spentTransactionId": null,
      "mainChain": true
    },
    {
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      "index": 3,
      "globalIndex": 53172946,
      "creationHeight": 1707322,
      "settlementHeight": 1707323,
      "ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
      "address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
      "assets": [
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          "decimals": 0,
          "type": "EIP-004"
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