Ad
Inputs (3)
Output transaction:
Settlement height:
Value:
0.25 ERG
Output transaction:
Settlement height:
Value:
0.203 ERG
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Outputs (4)
Spent in transaction:
Settlement height:
Value:
0.3 ERG
Spent in transaction:
Settlement height:
Value:
0.151 ERG
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Status: Confirmed
Size: 3.75 KB
Received time: 12/10/2025 04:51:47 PM
Included in blocks: 1,674,702
Confirmations: 94,581
Total coins transferred: 0.454 ERG
Fees: 0.002 ERG
Fees per byte: 0.00000052 ERG
Raw Transaction Data
{
  "id": "51e28f95a0f94f110fca1dc30f53074c3445b2359fe7e2cb17420c98e0371288",
  "blockId": "7d02e11c76ef92a494b9720712cf87f98d0287619ad8528aa77b41ff035ca696",
  "inclusionHeight": 1674702,
  "timestamp": 1765385507139,
  "index": 7,
  "globalIndex": 9942844,
  "numConfirmations": 94581,
  "inputs": [
    {
      "boxId": "963abe29d3712ac43b05c14cb36a79f3cb4035f0fbd3f2fef4f7a9a1b7ed0832",
      "value": 250000000,
      "index": 0,
      "spendingProof": "8baf5c3269ba7e40d533f167eddaa6a20e5ea061dfa6efee188dd0063237fbcc43963b4ded7c0280aaf73c8e58c3ce9215e522ba472f09e6",
      "outputBlockId": "24e02f10586da78d18e2c4a1cd82379bf409fc7b1c8c7022f917a044e09bed02",
      "outputTransactionId": "446100b7409caf5a81fdf7ee002f1648b9877e552ca10bfc6facf4ac46b9de03",
      "outputIndex": 0,
      "outputGlobalIndex": 52157846,
      "outputCreatedAt": 1674664,
      "outputSettledAt": 1674665,
      "ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
      "address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e20de05a701a23f3433481d0c8b27cac5fbfaafeba1605aa70f254ac37f7fd78d43",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "de05a701a23f3433481d0c8b27cac5fbfaafeba1605aa70f254ac37f7fd78d43"
        }
      }
    },
    {
      "boxId": "fe3a93f9bfc5a3270a5d5fa528bcf5025773c1fc72fb0e287bf9355ac8cb3045",
      "value": 203000000,
      "index": 1,
      "spendingProof": "ca3ef4099899399ad725e146dceccce410e10141a951790e1109570084b5ae152bed755027bb0a0c32dae798a8c4614281d6eaa4816dbc79",
      "outputBlockId": "fbe8a805b8b145acd439992edefd518916ee2eeaaa8ccdc354821b9588a3ee03",
      "outputTransactionId": "151d4066a074f7340ee816957b9aa392f80d8ce30f5bb20f6b8d57cc322ea272",
      "outputIndex": 1,
      "outputGlobalIndex": 52158757,
      "outputCreatedAt": 1674695,
      "outputSettledAt": 1674698,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(101,81,-78,-96,-104,100,-29,-117,-56,117,-114,-31,69,-111,49,96,-128,119,75,105,-64,-15,92,-47,41,58,-58,-79,41,8,99,-27)\n3: 3\n4: 0\n5: 0\n6: 0\n7: CBigInt(10000000000000000)\n8: 0\n9: 0\n10: Coll(70,-110,-119,24,-65,0,35,-37,-48,-39,6,89,39,119,-8,-13,-76,2,-38,-70,19,-128,114,35,-33,-23,11,101,87,74,38,-54)\n11: 0\n12: 1\n13: 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)\n14: 0\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 1000\n22: 6\n23: 0\n24: 0\n25: 0\n26: 0\n27: 0\n28: 0\n29: 1\n30: 2\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0\n36: 1\n37: 10000000\n38: 1\n39: 1000000\n40: 1000\n41: 1000\n42: 1000000\n43: 10000000\n44: 5\n45: 1000000\n46: 10000000\n47: 100000000\n48: 100000000\n49: 0\n50: 0\n51: 0\n52: 100000000\n53: 0\n54: 1\n55: 3\n56: 2\n57: 3\n58: 1000\n59: 1\n60: 1\n61: 980000\n62: 1000000\n63: CBigInt(1)\n64: 0\n65: 0\n66: 0\n67: 0\n68: -1\n69: 1\n70: 1\n71: 2000000\n72: 0\n73: 0\n74: 0\n75: true\n76: 0\n77: 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 = SELF.R9[Coll[Long]].get\n  val l6 = coll5(placeholder[Int](3))\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 coll12 = SELF.R8[Coll[Byte]].get\n  val l13 = SELF.R6[Long].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(placeholder[Int](5), SELF)\n  val coll18 = box17.tokens\n  val tuple19 = coll18(placeholder[Int](6))\n  val l20 = tuple19._2\n  val bi21 = placeholder[BigInt](7)\n  val bi22 = CONTEXT.dataInputs.filter({(box22: Box) =>\n      val coll24 = box22.tokens\n      (coll24.size > placeholder[Int](8)) && (coll24(placeholder[Int](9))._1 == placeholder[Coll[Byte]](10))\n    })(placeholder[Int](11)).R5[BigInt].get\n  val l23 = tuple8._2\n  val bi24 = l23.toBigInt\n  val coll25 = coll7.slice(placeholder[Int](12), coll7.size)\n  val coll26 = placeholder[Coll[Byte]](13)\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(placeholder[Int](14), SELF)\n  val coll30 = box29.tokens\n  val tuple31 = coll30(placeholder[Int](15))\n  val l32 = coll5(placeholder[Int](16))\n  val bool33 = INPUTS.filter({(box33: Box) => box33.propositionBytes == coll3 }).size == placeholder[Int](17)\n  val l34 = HEIGHT.toLong\n  val l35 = coll5(placeholder[Int](18)) + coll5(placeholder[Int](19))\n  val l36 = coll5(placeholder[Int](20))\n  val bi37 = bi24 * bi22 / bi21\n  val bi38 = if (l34 < l35) {(\n    val i38 = placeholder[Int](21)\n    bi37 * coll5(placeholder[Int](22)).toBigInt + i38.toBigInt / i38.toBigInt\n  )} else { bi37 }\n  val box39 = coll28.getOrElse(placeholder[Int](23), SELF)\n  val coll40 = box39.tokens\n  val tuple41 = coll40(placeholder[Int](24))\n  val func42 = {(box42: Box) =>\n    val coll44 = box42.propositionBytes\n    val coll45 = blake2b256(coll44)\n    val bool46 = coll45 == coll4\n    bool46\n  }\n  val coll43 = OUTPUTS.filter(func42)\n  val box44 = coll43.getOrElse(placeholder[Int](25), SELF)\n  val coll45 = box44.tokens\n  val tuple46 = coll45(placeholder[Int](26))\n  if (coll2.size > placeholder[Int](27)) {(\n    val func47 = func15\n    val coll48 = coll16\n    val func49 = func27\n    val coll50 = coll28\n    val box51 = coll2.getOrElse(placeholder[Int](28), SELF)\n    val coll52 = box51.R4[Coll[Long]].get\n    val l53 = coll52(placeholder[Int](29))\n    val l54 = coll52(placeholder[Int](30))\n    if (coll48.size > placeholder[Int](31)) {(\n      val box55 = box17\n      val l56 = box55.value\n      val coll57 = coll18\n      val tuple58 = tuple19\n      val coll59 = box55.R8[Coll[Byte]].get\n      val bool60 = (\n        (\n          ((((l56 >= l6) && (tuple58._1 == coll9)) && (box55.R4[Coll[Byte]].get == coll10)) && (box55.R5[GroupElement].get == ge11)) && (\n            box55.R7[Coll[Byte]].get == coll1\n          )\n        ) && (coll12 == coll59)\n      ) && (\n        OUTPUTS.map({(box60: Box) => box60.id }).indexOf(box55.id, placeholder[Int](32)) == box51.R9[Coll[Int]].get(placeholder[Int](33)) - placeholder[Int](34)\n      )\n      val l61 = box55.R6[Long].get\n      val coll62 = box55.R9[Coll[Long]].get\n      val bool63 = coll62 == coll5\n      if (coll50.size > placeholder[Int](35)) {(\n        val bi64 = l20.toBigInt\n        val box65 = box29\n        val coll66 = coll30\n        val tuple67 = coll66(placeholder[Int](36))\n        val tuple68 = tuple31\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (((bool60 && (l56 >= l14)) && (l56 <= l14 + placeholder[Long](37))) && (bi64 >= bi24 - tuple67._2.toBigInt * bi21 / bi22)) && (\n                          coll57.slice(placeholder[Int](38), coll57.size) == coll25\n                        )\n                      ) && (l61 == l13)\n                    ) && bool63\n                  ) && (((box65.value >= placeholder[Long](39)) && (tuple68._1 == coll9)) && (tuple67._1 == coll26))\n                ) && (tuple68._2 == l23 - l20)\n              ) && (l53.toBigInt >= bi64 * bi22 / bi21 * l32.toBigInt / placeholder[Int](40).toBigInt)\n            ) && bool33\n          ) && (l34 >= l35)\n        )\n      )} else {(\n        val bi64 = l53.toBigInt\n        val i65 = placeholder[Int](41)\n        val bi66 = l20.toBigInt * bi22 / bi21 * l32.toBigInt / i65.toBigInt\n        val bool67 = bi64 >= bi66\n        sigmaProp(\n          (\n            (\n              (\n                ((((bool60 && (l56 >= l14 - placeholder[Long](42))) && (l56 <= l14 + placeholder[Long](43))) && (coll57 == coll7)) && (l61 > l34 + l36)) && (\n                  l61 < l34 + l36 + placeholder[Long](44)\n                )\n              ) && (bi64 < bi66)\n            ) && bool63\n          ) && bool33\n        ) || sigmaProp(\n          (\n            (\n              (\n                (\n                  (((bool60 && (l56 >= l14 - placeholder[Long](45))) && (l56 <= l14 + placeholder[Long](46))) && (coll57 == coll7)) && (\n                    l13 != placeholder[Long](47)\n                  )\n                ) && (l61 == placeholder[Long](48))\n              ) && bool67\n            ) && bool63\n          ) && bool33\n        ) || sigmaProp(INPUTS.filter({(box68: Box) =>\n              val coll70 = box68.tokens\n              (coll70.size > placeholder[Int](49)) && (coll70(placeholder[Int](50))._1 == coll59)\n            }).size > placeholder[Int](51)) || proveDlog(ge11) && sigmaProp(\n          (\n            (\n              (\n                ((((bool60 && (bi64 >= bi38 * l54.toBigInt / i65.toBigInt)) && (tuple58 == tuple8)) && (l61 == placeholder[Long](52))) && bool67) && (\n                  (coll62(placeholder[Int](53)) == l54) && (coll62(placeholder[Int](54)) == coll52(placeholder[Int](55)))\n                )\n              ) && bool33\n            ) && (coll62(placeholder[Int](56)) == l36)\n          ) && (coll62(placeholder[Int](57)) == l6)\n        )\n      )}\n    )} else {(\n      val bi55 = l53.toBigInt\n      val i56 = placeholder[Int](58)\n      val box57 = box39\n      val coll58 = coll40\n      val tuple59 = tuple41\n      val tuple60 = coll58(placeholder[Int](59))\n      val coll61 = SELF.id\n      val bi62 = bi55 - bi38\n      val bi63 = coll5(placeholder[Int](60)).toBigInt\n      val bi64 = bi62 * i56.toBigInt - bi63 / i56.toBigInt\n      val l65 = tuple60._2\n      sigmaProp(\n        (\n          (\n            (\n              (\n                (((bi55 <= bi38 * l32.toBigInt / i56.toBigInt) && (l34 >= l13)) || (l34 > SELF.creationInfo._1.toLong + placeholder[Long](61))) && (\n                  (((box57.value >= placeholder[Long](62)) && (tuple59._1 == coll9)) && (tuple60._1 == coll26)) && (box57.id != coll61)\n                )\n              ) && (tuple59._2 == l23)\n            ) && if (bi64 < placeholder[BigInt](63)) { l65.toBigInt >= bi55 } else {(\n              val box66 = OUTPUTS.filter({(box66: Box) => box66.propositionBytes == coll10 }).getOrElse(placeholder[Int](64), SELF)\n              val tuple67 = box66.tokens(placeholder[Int](65))\n              (((l65.toBigInt >= bi38 + bi62 * bi63 / i56.toBigInt) && (tuple67._2.toBigInt >= bi64)) && (tuple67._1 == coll26)) && (box66.id != coll61)\n            )}\n          ) && (\n            INPUTS.map({(box66: Box) => box66.id }).indexOf(coll61, placeholder[Int](66)) == box51.R9[Coll[Int]].get(placeholder[Int](67)) * placeholder[Int](\n              68\n            ) - placeholder[Int](69)\n          )\n        ) && bool33\n      )\n    )}\n  )} else {(\n    val func47 = func42\n    val coll48 = coll43\n    val box49 = box44\n    val coll50 = coll45\n    val tuple51 = tuple46\n    val tuple52 = coll50(placeholder[Int](70))\n    sigmaProp(\n      (\n        (\n          (((((box49.value >= placeholder[Long](71)) && (tuple51._1 == coll9)) && (tuple52._1 == coll26)) && (box49.id != SELF.id)) && (tuple51._2 == l23)) && (\n            tuple52._2.toBigInt > bi38\n          )\n        ) && if (INPUTS.filter({(box53: Box) =>\n            val coll55 = box53.tokens\n            (coll55.size > placeholder[Int](72)) && (coll55(placeholder[Int](73))._1 == coll12)\n          }).size > placeholder[Int](74)) { placeholder[Boolean](75) } else {(\n          val box53 = OUTPUTS.filter({(box53: Box) => box53.propositionBytes == coll10 }).getOrElse(placeholder[Int](76), SELF)\n          ((box53.value >= l14 - placeholder[Long](77)) && (box53.tokens == coll25)) && (box53.id != SELF.id)\n        )}\n      ) && bool33\n    )\n  )}\n}",
      "address": "DDB7tcAQH38nPrnVpqaGDt4i2m9dEknWkZrSymCyseLLeN4rgA7ZnkcCxQecF1hnz2xyoABU4vgzpwfDL5ho7p2rq6iMWCN9A7aLm9z1RNWCeuQt6JSsCAW36exKvjNMJVDMsT7t27VriVqHrkxoSguzr3XCVgPu2MnbesMzdiF1Wb2Xz1Cop2H4YA8GPcPaWFBFSh7BF4PDHH4cVVfrPGmPtWdL8SnHSHtA7Pb8TyWVr3wP5XRwxnJt7ESWnmNfqQFfRARCoQF5zoUtVMCdYZAtHNYE9BwJvtwKVtrqtasNPRDmu9PEZBP9g3arJvcvFMzVFXWBaWM376nq749XYKuTo6WnWrBvf8cFM4eDbpKrkT2GtEAQYTurMsnBhKiABmrFwEXvfWqR6P39YoWWM7McrLRBPAuLvH4Nt6a7wT5fPgUShnK6rHHbCcMaFRYqJ7MAPmzqSEs1AiZNRiwCifk4rCDdLCjJ2tthx4bNM5aY66EqnVeaKVZZXNJ9YeciEaMW5jJA5Kxd2X3kMkFp6LzCEp7CC923pCnpF525SqHDR8qK33Epmo6Nzge4gEEgriA5vvM9ZwKqHRXCHnByXATkRdMgKXc9cEQtgcxkP6SAco2TpLxriKvHmULge4oHuuLXzEE67DyHjqcoJ63zSgHMc6wscBaXYuvpLqFb64QrJPEgB2fTEQpp3yWGfMcrKLuhmRgXrnGNfKUNoDHr81DYyeZv4cbvfnhQu7hJZM7Hxa52Riyn3N37amQztjMrdTCTYDdRie6purW3jdo8QNQJvQSYr9CtbvfbStqXayHhxt19E2wwCom2uJ4WVDzX5VG2A2ofx9c62hh8U1QeknCgck5g86JN72bKFWUw6ekHvLt2VP4Cojv37yzPe2ZNtaobLRXnuUdfyuhiCoTWvpti15GztZVen1pQnRoANnYMjSvkfbmYrpW3qGZN4nFttfDNPR8J4bLZTwQP27uvuKtS5XnipFBqpB9JQTJ1HQjxEigdcUb49QpLBP6reNAeZrSx9ezD2nKxCsqGy6Zd15YUCUBaeuCryRfDAHs8HV7RMbackwr35D8wq9qMxQXaDtw82EKqM4rTrnCwU8bC4AVmfMmYEt92EZibaJvawxUhHC5FYDqQnSDvJ6MhC8jRTMNz1Zf9U2LhGwmVYuhBb2PbmC8Ef9jA8sVDC3taATHjXtGrSuaC7xw4JSakaUg89XkqTcCZ76uiU8RvRhfwCjdb8AifywzeHBWUfVoPgZDDowDgmtyymFqdWt3VV48QutwNipPu9WC1p8hy63BBRBnSULnhF8uVRqATebjdRF7tLzS8wUFhc8KrS2SeqiWDnKcN3o4AZXqZKJBiUaFiBBXu7WAyApDqkKScnZ6ob5i6TYsJrUo7X3n7C31FnB8WKf6ghQT5nsfBYdEF4f6bB6KZf2dowgNxPaC8QCuZLbrVUzj5WL38k29AYNuwNeotZHz55V7fmczqD4dsdGSQwXyNu6fLePzLbxoF1MCBMSrsaGmoeRvEzVtogFHvg2dDk5KfujjixdkJZKvXTfwFfV5q1ATiksnTHhesa2Wsfn9AUUPBHHhVrk7bp2tMitPwQrTLvRAXTXUc2x8NUWGeTWcE43Q9eQH8yXZf63jxw8EUiNzfC3TbLndMn3rcrjWZCbLqht8xPo8YGqxcXdHhAMN13YBt1T21yHA8Jb3X3ipYYj4hNzhBraky3Ue6P9nrfhwTD1HceB8hV4Htx3DCAd7PG86ejZphEUcoRv1Sjrfb3wahW6yKu8jkPJBKRuyRoMxoGwDnjAbRdnZ4gYzhtJ2Luu44Qu63kmHBzBkjeohf1BhDcYTcgqsJ8dnLGzdjxWcPUqJmKiFLWALD4enaEEAebLFnGCy5xDdNxBuFW7NWYxLKWMkyd2yHU7dgZjSURe29eFnHNEaJYiFyJGPvV2Q8ErYq82Q7VcGYb8K2A5ftcfsgpVb3tfYitQdo6jvg7XmXFi1Ps9Z3tyHQ2U3rbLrqMKFvHAMCeYJoQ7sknAUgbvqx6k5kF8cmabtUq94ZzaHoDPUpVTqQaHskN5ggwztTEpm7CK9v4uM3T7nDbUi4h9PrB9nVMEboMJQxHCpho2y1A38bULqL8SfZzTWiyA2ed3S6XisJKyNPUtVkau3Ljehsz2m1nFvwWTHWkiCCwJpQBWi1bbgp4LAWhsvsHXxNoX4LbVtuoMwko45hUjdbgMZb4CHMTtCUVEayywb8YYrZekZxVZN6wKzcXU5qemp4xkNeVrWxQpU37p8MR84CE2HfFPjAsBdDkcofWcjECtJf1trayRrKwqurGW9i2eD62i2zkxKEv4Fis3ZzNj2ofRdZV723m9YLQqFPcaJeWFQPLGCCj6KtR5TXkM83itoaWjNaDzjAghoMB4S6LjyyNnyqdSzybuCq4n1NcUH83NCSD5uc2aRMxUni2tzPtLmNZdAMRnhf2Cmn5yN9kuXhWPSBWqTmdgy17h5wsjb3YghxcP3fwzLym7EjJJn1vxseV7wwksoUhCjfVia7hpZnoD9ULoEBjatePkDRVcKvXCwC",
      "assets": [
        {
          "tokenId": "5111745356473bad65df3cd53dcbafb0fa76b770a9982a923e3894333bacf642",
          "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": "0e20d82a3ad5af62a4c4fa2f142dac14024151f1a4a2ad134c8e3d1313b3be8d75c3",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "d82a3ad5af62a4c4fa2f142dac14024151f1a4a2ad134c8e3d1313b3be8d75c3"
        },
        "R9": {
          "serializedValue": "1108b6163c108087a70e0098b7cc01641e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1435,30,8,15000000,0,1674700,50,15]"
        },
        "R4": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        }
      }
    },
    {
      "boxId": "f3e246c4cd474a1e7f75ed7ec8c0c56b03a9f82b659c2bd81025b2f5dfabbe00",
      "value": 1000000,
      "index": 2,
      "spendingProof": null,
      "outputBlockId": "fbe8a805b8b145acd439992edefd518916ee2eeaaa8ccdc354821b9588a3ee03",
      "outputTransactionId": "151d4066a074f7340ee816957b9aa392f80d8ce30f5bb20f6b8d57cc322ea272",
      "outputIndex": 3,
      "outputGlobalIndex": 52158759,
      "outputCreatedAt": 1674695,
      "outputSettledAt": 1674698,
      "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": "d82a3ad5af62a4c4fa2f142dac14024151f1a4a2ad134c8e3d1313b3be8d75c3",
          "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": "110a80a0b787e905aaf8a610b6163c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,17096213,1435,30,15000000,8,0,50,15,20000000]"
        }
      }
    }
  ],
  "dataInputs": [
    {
      "boxId": "5baa304706813a5c6f4a5608efa914eca2a19ddb3c7c73d4134c680112f0f30b",
      "value": 1000000,
      "index": 0,
      "outputBlockId": "bf1dbabcd3891b42e02928658bb4fa93af0e047ab93de0bb51930d0ce55f65a0",
      "outputTransactionId": "0b0407c88519294b1b7171c565f378b5e586fd402e075ebdc6b515fdfaf7462e",
      "outputIndex": 0,
      "ergoTree": "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",
      "address": "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",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "05f090cc01",
          "sigmaType": "SLong",
          "renderedValue": "1672248"
        },
        "R5": {
          "serializedValue": "06072386f26fc10000",
          "sigmaType": "SBigInt",
          "renderedValue": "CBigInt(10000000000000000)"
        }
      }
    },
    {
      "boxId": "4490ec1719b975c12b4866c62de5f8fa5148fb0712b680146df4968635c775fa",
      "value": 15643757938063,
      "index": 1,
      "outputBlockId": "6acf5543eef1ad8f05aa02db74dad828b819a697c8e0b88fd26878665cfc3d10",
      "outputTransactionId": "29b376c76b58ea56fbcf7677bfea802d77cd9a5c3549d0267b7eec0d24e057dd",
      "outputIndex": 0,
      "ergoTree": "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",
      "address": "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",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "04ca0f",
          "sigmaType": "SInt",
          "renderedValue": "997"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "2d2b4e4195800c3108e9c7eb084216c6d5f4237557087a55cae92a6995e53eee",
      "transactionId": "51e28f95a0f94f110fca1dc30f53074c3445b2359fe7e2cb17420c98e0371288",
      "blockId": "7d02e11c76ef92a494b9720712cf87f98d0287619ad8528aa77b41ff035ca696",
      "value": 300000000,
      "index": 0,
      "globalIndex": 52158880,
      "creationHeight": 1674699,
      "settlementHeight": 1674702,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(101,81,-78,-96,-104,100,-29,-117,-56,117,-114,-31,69,-111,49,96,-128,119,75,105,-64,-15,92,-47,41,58,-58,-79,41,8,99,-27)\n3: 3\n4: 0\n5: 0\n6: 0\n7: CBigInt(10000000000000000)\n8: 0\n9: 0\n10: Coll(70,-110,-119,24,-65,0,35,-37,-48,-39,6,89,39,119,-8,-13,-76,2,-38,-70,19,-128,114,35,-33,-23,11,101,87,74,38,-54)\n11: 0\n12: 1\n13: 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)\n14: 0\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 1000\n22: 6\n23: 0\n24: 0\n25: 0\n26: 0\n27: 0\n28: 0\n29: 1\n30: 2\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0\n36: 1\n37: 10000000\n38: 1\n39: 1000000\n40: 1000\n41: 1000\n42: 1000000\n43: 10000000\n44: 5\n45: 1000000\n46: 10000000\n47: 100000000\n48: 100000000\n49: 0\n50: 0\n51: 0\n52: 100000000\n53: 0\n54: 1\n55: 3\n56: 2\n57: 3\n58: 1000\n59: 1\n60: 1\n61: 980000\n62: 1000000\n63: CBigInt(1)\n64: 0\n65: 0\n66: 0\n67: 0\n68: -1\n69: 1\n70: 1\n71: 2000000\n72: 0\n73: 0\n74: 0\n75: true\n76: 0\n77: 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 = SELF.R9[Coll[Long]].get\n  val l6 = coll5(placeholder[Int](3))\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 coll12 = SELF.R8[Coll[Byte]].get\n  val l13 = SELF.R6[Long].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(placeholder[Int](5), SELF)\n  val coll18 = box17.tokens\n  val tuple19 = coll18(placeholder[Int](6))\n  val l20 = tuple19._2\n  val bi21 = placeholder[BigInt](7)\n  val bi22 = CONTEXT.dataInputs.filter({(box22: Box) =>\n      val coll24 = box22.tokens\n      (coll24.size > placeholder[Int](8)) && (coll24(placeholder[Int](9))._1 == placeholder[Coll[Byte]](10))\n    })(placeholder[Int](11)).R5[BigInt].get\n  val l23 = tuple8._2\n  val bi24 = l23.toBigInt\n  val coll25 = coll7.slice(placeholder[Int](12), coll7.size)\n  val coll26 = placeholder[Coll[Byte]](13)\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(placeholder[Int](14), SELF)\n  val coll30 = box29.tokens\n  val tuple31 = coll30(placeholder[Int](15))\n  val l32 = coll5(placeholder[Int](16))\n  val bool33 = INPUTS.filter({(box33: Box) => box33.propositionBytes == coll3 }).size == placeholder[Int](17)\n  val l34 = HEIGHT.toLong\n  val l35 = coll5(placeholder[Int](18)) + coll5(placeholder[Int](19))\n  val l36 = coll5(placeholder[Int](20))\n  val bi37 = bi24 * bi22 / bi21\n  val bi38 = if (l34 < l35) {(\n    val i38 = placeholder[Int](21)\n    bi37 * coll5(placeholder[Int](22)).toBigInt + i38.toBigInt / i38.toBigInt\n  )} else { bi37 }\n  val box39 = coll28.getOrElse(placeholder[Int](23), SELF)\n  val coll40 = box39.tokens\n  val tuple41 = coll40(placeholder[Int](24))\n  val func42 = {(box42: Box) =>\n    val coll44 = box42.propositionBytes\n    val coll45 = blake2b256(coll44)\n    val bool46 = coll45 == coll4\n    bool46\n  }\n  val coll43 = OUTPUTS.filter(func42)\n  val box44 = coll43.getOrElse(placeholder[Int](25), SELF)\n  val coll45 = box44.tokens\n  val tuple46 = coll45(placeholder[Int](26))\n  if (coll2.size > placeholder[Int](27)) {(\n    val func47 = func15\n    val coll48 = coll16\n    val func49 = func27\n    val coll50 = coll28\n    val box51 = coll2.getOrElse(placeholder[Int](28), SELF)\n    val coll52 = box51.R4[Coll[Long]].get\n    val l53 = coll52(placeholder[Int](29))\n    val l54 = coll52(placeholder[Int](30))\n    if (coll48.size > placeholder[Int](31)) {(\n      val box55 = box17\n      val l56 = box55.value\n      val coll57 = coll18\n      val tuple58 = tuple19\n      val coll59 = box55.R8[Coll[Byte]].get\n      val bool60 = (\n        (\n          ((((l56 >= l6) && (tuple58._1 == coll9)) && (box55.R4[Coll[Byte]].get == coll10)) && (box55.R5[GroupElement].get == ge11)) && (\n            box55.R7[Coll[Byte]].get == coll1\n          )\n        ) && (coll12 == coll59)\n      ) && (\n        OUTPUTS.map({(box60: Box) => box60.id }).indexOf(box55.id, placeholder[Int](32)) == box51.R9[Coll[Int]].get(placeholder[Int](33)) - placeholder[Int](34)\n      )\n      val l61 = box55.R6[Long].get\n      val coll62 = box55.R9[Coll[Long]].get\n      val bool63 = coll62 == coll5\n      if (coll50.size > placeholder[Int](35)) {(\n        val bi64 = l20.toBigInt\n        val box65 = box29\n        val coll66 = coll30\n        val tuple67 = coll66(placeholder[Int](36))\n        val tuple68 = tuple31\n        sigmaProp(\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (((bool60 && (l56 >= l14)) && (l56 <= l14 + placeholder[Long](37))) && (bi64 >= bi24 - tuple67._2.toBigInt * bi21 / bi22)) && (\n                          coll57.slice(placeholder[Int](38), coll57.size) == coll25\n                        )\n                      ) && (l61 == l13)\n                    ) && bool63\n                  ) && (((box65.value >= placeholder[Long](39)) && (tuple68._1 == coll9)) && (tuple67._1 == coll26))\n                ) && (tuple68._2 == l23 - l20)\n              ) && (l53.toBigInt >= bi64 * bi22 / bi21 * l32.toBigInt / placeholder[Int](40).toBigInt)\n            ) && bool33\n          ) && (l34 >= l35)\n        )\n      )} else {(\n        val bi64 = l53.toBigInt\n        val i65 = placeholder[Int](41)\n        val bi66 = l20.toBigInt * bi22 / bi21 * l32.toBigInt / i65.toBigInt\n        val bool67 = bi64 >= bi66\n        sigmaProp(\n          (\n            (\n              (\n                ((((bool60 && (l56 >= l14 - placeholder[Long](42))) && (l56 <= l14 + placeholder[Long](43))) && (coll57 == coll7)) && (l61 > l34 + l36)) && (\n                  l61 < l34 + l36 + placeholder[Long](44)\n                )\n              ) && (bi64 < bi66)\n            ) && bool63\n          ) && bool33\n        ) || sigmaProp(\n          (\n            (\n              (\n                (\n                  (((bool60 && (l56 >= l14 - placeholder[Long](45))) && (l56 <= l14 + placeholder[Long](46))) && (coll57 == coll7)) && (\n                    l13 != placeholder[Long](47)\n                  )\n                ) && (l61 == placeholder[Long](48))\n              ) && bool67\n            ) && bool63\n          ) && bool33\n        ) || sigmaProp(INPUTS.filter({(box68: Box) =>\n              val coll70 = box68.tokens\n              (coll70.size > placeholder[Int](49)) && (coll70(placeholder[Int](50))._1 == coll59)\n            }).size > placeholder[Int](51)) || proveDlog(ge11) && sigmaProp(\n          (\n            (\n              (\n                ((((bool60 && (bi64 >= bi38 * l54.toBigInt / i65.toBigInt)) && (tuple58 == tuple8)) && (l61 == placeholder[Long](52))) && bool67) && (\n                  (coll62(placeholder[Int](53)) == l54) && (coll62(placeholder[Int](54)) == coll52(placeholder[Int](55)))\n                )\n              ) && bool33\n            ) && (coll62(placeholder[Int](56)) == l36)\n          ) && (coll62(placeholder[Int](57)) == l6)\n        )\n      )}\n    )} else {(\n      val bi55 = l53.toBigInt\n      val i56 = placeholder[Int](58)\n      val box57 = box39\n      val coll58 = coll40\n      val tuple59 = tuple41\n      val tuple60 = coll58(placeholder[Int](59))\n      val coll61 = SELF.id\n      val bi62 = bi55 - bi38\n      val bi63 = coll5(placeholder[Int](60)).toBigInt\n      val bi64 = bi62 * i56.toBigInt - bi63 / i56.toBigInt\n      val l65 = tuple60._2\n      sigmaProp(\n        (\n          (\n            (\n              (\n                (((bi55 <= bi38 * l32.toBigInt / i56.toBigInt) && (l34 >= l13)) || (l34 > SELF.creationInfo._1.toLong + placeholder[Long](61))) && (\n                  (((box57.value >= placeholder[Long](62)) && (tuple59._1 == coll9)) && (tuple60._1 == coll26)) && (box57.id != coll61)\n                )\n              ) && (tuple59._2 == l23)\n            ) && if (bi64 < placeholder[BigInt](63)) { l65.toBigInt >= bi55 } else {(\n              val box66 = OUTPUTS.filter({(box66: Box) => box66.propositionBytes == coll10 }).getOrElse(placeholder[Int](64), SELF)\n              val tuple67 = box66.tokens(placeholder[Int](65))\n              (((l65.toBigInt >= bi38 + bi62 * bi63 / i56.toBigInt) && (tuple67._2.toBigInt >= bi64)) && (tuple67._1 == coll26)) && (box66.id != coll61)\n            )}\n          ) && (\n            INPUTS.map({(box66: Box) => box66.id }).indexOf(coll61, placeholder[Int](66)) == box51.R9[Coll[Int]].get(placeholder[Int](67)) * placeholder[Int](\n              68\n            ) - placeholder[Int](69)\n          )\n        ) && bool33\n      )\n    )}\n  )} else {(\n    val func47 = func42\n    val coll48 = coll43\n    val box49 = box44\n    val coll50 = coll45\n    val tuple51 = tuple46\n    val tuple52 = coll50(placeholder[Int](70))\n    sigmaProp(\n      (\n        (\n          (((((box49.value >= placeholder[Long](71)) && (tuple51._1 == coll9)) && (tuple52._1 == coll26)) && (box49.id != SELF.id)) && (tuple51._2 == l23)) && (\n            tuple52._2.toBigInt > bi38\n          )\n        ) && if (INPUTS.filter({(box53: Box) =>\n            val coll55 = box53.tokens\n            (coll55.size > placeholder[Int](72)) && (coll55(placeholder[Int](73))._1 == coll12)\n          }).size > placeholder[Int](74)) { placeholder[Boolean](75) } else {(\n          val box53 = OUTPUTS.filter({(box53: Box) => box53.propositionBytes == coll10 }).getOrElse(placeholder[Int](76), SELF)\n          ((box53.value >= l14 - placeholder[Long](77)) && (box53.tokens == coll25)) && (box53.id != SELF.id)\n        )}\n      ) && bool33\n    )\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "5111745356473bad65df3cd53dcbafb0fa76b770a9982a923e3894333bacf642",
          "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": "0e20d82a3ad5af62a4c4fa2f142dac14024151f1a4a2ad134c8e3d1313b3be8d75c3",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "d82a3ad5af62a4c4fa2f142dac14024151f1a4a2ad134c8e3d1313b3be8d75c3"
        },
        "R9": {
          "serializedValue": "11089e163c108087a70e0098b7cc01641e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1423,30,8,15000000,0,1674700,50,15]"
        },
        "R4": {
          "serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
        }
      },
      "spentTransactionId": "d0761d64459ac950d5a31bf5e6262223bf886cd68f41eb117285b30d42cdb09e",
      "mainChain": true
    },
    {
      "boxId": "acf7b0020c22e14ce1bdcc51c505eed2f0d217da207617c7fef927cde6203fc6",
      "transactionId": "51e28f95a0f94f110fca1dc30f53074c3445b2359fe7e2cb17420c98e0371288",
      "blockId": "7d02e11c76ef92a494b9720712cf87f98d0287619ad8528aa77b41ff035ca696",
      "value": 151000000,
      "index": 1,
      "globalIndex": 52158881,
      "creationHeight": 1674699,
      "settlementHeight": 1674702,
      "ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
      "address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "ff3457dfdf7e22f0f8d65d6296317ef9fe0d30a6013633a9b51e229b5c482b4c",
      "mainChain": true
    },
    {
      "boxId": "12c0e01942a86942bf17cdf69f3616f3f95f440fd399e6ec6254eb4495652a63",
      "transactionId": "51e28f95a0f94f110fca1dc30f53074c3445b2359fe7e2cb17420c98e0371288",
      "blockId": "7d02e11c76ef92a494b9720712cf87f98d0287619ad8528aa77b41ff035ca696",
      "value": 1000000,
      "index": 2,
      "globalIndex": 52158882,
      "creationHeight": 1674699,
      "settlementHeight": 1674702,
      "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": "d82a3ad5af62a4c4fa2f142dac14024151f1a4a2ad134c8e3d1313b3be8d75c3",
          "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": "110a80a0b787e905e8a7a5189e163c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,25471476,1423,30,15000000,8,0,50,15,20000000]"
        }
      },
      "spentTransactionId": "d0761d64459ac950d5a31bf5e6262223bf886cd68f41eb117285b30d42cdb09e",
      "mainChain": true
    },
    {
      "boxId": "127b0870871f1ceae6aebbd761fb9f96e3b9088211875fb0a1b6df26c30382a6",
      "transactionId": "51e28f95a0f94f110fca1dc30f53074c3445b2359fe7e2cb17420c98e0371288",
      "blockId": "7d02e11c76ef92a494b9720712cf87f98d0287619ad8528aa77b41ff035ca696",
      "value": 2000000,
      "index": 3,
      "globalIndex": 52158883,
      "creationHeight": 1674699,
      "settlementHeight": 1674702,
      "ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
      "ergoTreeScript": "{sigmaProp(\n  allOf(\n    Coll[Boolean](\n      HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n        placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n      ), OUTPUTS.size == placeholder[Int](4)\n    )\n  )\n)}",
      "address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "82440804cc426d52ff11f06e9eb6aa75b5dbcd6edad73cced1392fa34d0b0664",
      "mainChain": true
    }
  ],
  "size": 3844,
  "isUnconfirmed": false
}