{
  "boxId": "0ea1b5ba7382b3abf977d5d70bf2897695082a702181c075a05fa497e5bccede",
  "transactionId": "0f95cc6312b4a07b5315c5b67d80a5268828971f6a10365e61892ccd355ca0a0",
  "blockId": "ea13dcee6c841cbaf41df3a44428c1f58f759739ca0513801c3b460964774d29",
  "value": 4200000,
  "index": 0,
  "globalIndex": 25636030,
  "creationHeight": 918721,
  "settlementHeight": 918723,
  "ergoTree": "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",
  "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 1\n4: 3\n5: 1\n6: 0\n7: 0\n8: 2\n9: 100\n10: 0\n11: 7\n12: Coll(119,119,119,-27,5,31,-118,107,-61,8,39,-18,65,-35,57,-32,75,-54,29,-70,53,35,107,-102,38,-76,-108,-32,-70,-56,79,51)\n13: Coll(48)\n14: 1\n15: 2100000\n16: 1\n17: false\n18: 0\n19: 1\n20: 0\n21: 86400000\n22: 2\n23: 1\n24: 86400000\n25: 2100000\n26: 1\n27: 1\n28: 2\n29: 1\n30: 2100000\n31: 9\n32: false\n33: 14400000\n34: 2\n35: 0\n36: 0\n37: 0\n38: 0\n39: 0\n40: 100\n41: 500\n42: 1000\n43: 2000\n44: 4000\n45: 9000\n46: 13000\n47: 20000\n48: 30000\n49: 40000\n50: 50000\n51: 70000\n52: 110000\n53: 140000\n54: 170000\n55: 210000\n56: 250000\n57: 300000\n58: 500000\n59: 1\n60: 0\n61: 1\n62: 0\n63: 1\n64: 4\n65: 4\n66: 1775840000\n67: 0\n68: 5\n69: 1000\n70: 6\n71: 177584000\n72: 10000\n73: 0\n74: Coll(102,102,102,-116,-29,83,-2,-3,20,109,20,-76,20,-126,-43,38,-21,-14,106,90,125,32,79,54,87,12,89,-59,88,19,107,-125)\n75: 30\n76: 1\n77: 2\n78: 2\n79: 1000000\n80: 3\n81: 3\n82: 1000000\n83: 8\n84: 1000\n85: false\n86: 2\n87: 4\n88: 0\n89: 2\n90: 0\n91: false\n92: 1100000\n93: false",
  "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val tuple2 = (Coll[Byte](), placeholder[Long](0))\n  val tuple3 = coll1.getOrElse(placeholder[Int](1), tuple2)\n  val box4 = SELF.R7[Box].get\n  val bool5 = (tuple3._1 == box4.id) && (SELF.propositionBytes == box4.propositionBytes)\n  val box6 = if (bool5) { box4 } else { SELF }\n  val prop7 = box6.R9[SigmaProp].get\n  val bool8 = !bool5\n  val box9 = OUTPUTS(placeholder[Int](2))\n  val coll10 = box9.propositionBytes\n  val coll11 = SELF.propositionBytes\n  val box12 = OUTPUTS(placeholder[Int](3))\n  val coll13 = box6.R8[Coll[Long]].get\n  val l14 = coll13(placeholder[Int](4))\n  val l15 = CONTEXT.preHeader.timestamp\n  val l16 = l14 - l15\n  val coll17 = box9.tokens\n  val tuple18 = coll17.getOrElse(placeholder[Int](5), tuple2)\n  val l19 = tuple18._2\n  val l20 = tuple3._2\n  val bool21 = coll13(placeholder[Int](6)) == placeholder[Long](7)\n  val l22 = coll13(placeholder[Int](8))\n  val l23 = l22 * placeholder[Long](9)\n  val tuple24 = coll17.getOrElse(placeholder[Int](10), tuple2)\n  val l25 = tuple24._2\n  val l26 = SELF.value\n  val l27 = coll13(placeholder[Int](11))\n  val coll28 = tuple24._1\n  val coll29 = box6.id\n  val coll30 = placeholder[Coll[Byte]](12)\n  val coll31 = placeholder[Coll[Byte]](13)\n  val bool32 = if (coll10 == coll11) {\n    (\n      (\n        (\n          (\n            (((coll28 == coll29) && (l25 >= placeholder[Long](14))) && (box9.value >= placeholder[Long](15))) && (\n              ((bool21 && (tuple18._1 == coll30)) && (l19 >= placeholder[Long](16))) || (!bool21)\n            )\n          ) && (box9.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)\n        ) && (box9.R5[Coll[Byte]].get == coll31)\n      ) && (box9.R6[Coll[Byte]].get == coll31)\n    ) && (box9.R7[Box].get == box6)\n  } else { placeholder[Boolean](17) }\n  val coll33 = box6.R5[Coll[Byte]].get\n  val bool34 = l15 <= l14\n  val l35 = box9.value\n  val tuple36 = box12.tokens.getOrElse(placeholder[Int](18), tuple2)\n  val coll37 = tuple36._1\n  val l38 = tuple36._2\n  val coll39 = prop7.propBytes\n  val bool40 = coll13(placeholder[Int](19)) == placeholder[Long](20)\n  val bool41 = l15 > l14\n  val bool42 = if (bool40) { (bool5 && bool41) && (l15 < l14 + placeholder[Long](21)) } else { bool5 && bool34 }\n  prop7 && sigmaProp(((bool8 && (OUTPUTS.size == placeholder[Int](22))) && (coll10 != coll11)) && (box12.propositionBytes != coll11)) || sigmaProp(\n    (\n      (\n        if ((bool8 && (INPUTS.size == placeholder[Int](23))) && (l16 >= placeholder[Long](24))) {\n          (\n            (\n              bool32 && (\n                ((box9.value >= placeholder[Long](25)) && (box9.R7[Box].get == SELF)) && (\n                  (\n                    ((bool21 && (l19 == l20)) && (l25 == l20 - placeholder[Long](26) / l23 + placeholder[Long](27))) && (coll17.size == placeholder[Int](28))\n                  ) || (((!bool21) && (coll17.size == placeholder[Int](29))) && (l25 == l26 - placeholder[Long](30) / l27))\n                )\n              )\n            ) && (box12.propositionBytes == coll33)\n          ) && (box12.value >= coll13(placeholder[Int](31)))\n        } else { placeholder[Boolean](32) } || if (((!(bool34 && (l15 > l14 - placeholder[Long](33)))) && (INPUTS.size == placeholder[Int](34))) && (\n          CONTEXT.dataInputs.size > placeholder[Int](35)\n        )) {(\n          val box43 = CONTEXT.dataInputs(placeholder[Int](36))\n          val l44 = l20 - l25\n          val l45 = box43.R4[Long].get\n          val l46 = if (bool21) { max(placeholder[Long](37), l45 - l27 * l22) } else { max(placeholder[Long](38), l27 - l45 * l22) }\n          val coll47 = Coll[Long](\n            placeholder[Long](39), placeholder[Long](40), placeholder[Long](41), placeholder[Long](42), placeholder[Long](43), placeholder[Long](\n              44\n            ), placeholder[Long](45), placeholder[Long](46), placeholder[Long](47), placeholder[Long](48), placeholder[Long](49), placeholder[Long](\n              50\n            ), placeholder[Long](51), placeholder[Long](52), placeholder[Long](53), placeholder[Long](54), placeholder[Long](55), placeholder[Long](\n              56\n            ), placeholder[Long](57), placeholder[Long](58)\n          )\n          val coll48 = coll47.map({(l48: Long) => l48 * l48 }).zip(coll47)\n          val i49 = coll48.map({(tuple49: (Long, Long)) => if (tuple49._1 >= l16) { placeholder[Long](59) } else { placeholder[Long](60) } }).indexOf(\n            placeholder[Long](61), placeholder[Int](62)\n          )\n          val tuple50 = coll48(i49 - placeholder[Int](63))\n          val l51 = tuple50._2\n          val tuple52 = coll48(i49)\n          val l53 = tuple50._1\n          val l54 = l51 + tuple52._2 - l51 * l16 - l53 / tuple52._1 - l53\n          val l55 = placeholder[Long](64) * coll13(placeholder[Int](65)) * l22 * l27 * l54 / placeholder[Int](66).toLong\n          val l56 = max(placeholder[Long](67), l55 - l55 * coll13(placeholder[Int](68)) * max(l45 - l27, l27 - l45) / placeholder[Long](69) * l27)\n          val l57 = if (bool40) { l46 + l56 } else { l46 + l56 + l56 * coll13(placeholder[Int](70)) * l54 / placeholder[Int](71).toLong }\n          val l58 = l44 * l57 - l57 % placeholder[Long](72)\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (box43.tokens(placeholder[Int](73))._1 == placeholder[Coll[Byte]](74)) && (HEIGHT <= box43.R5[Int].get + placeholder[Int](75))\n                          ) && bool32\n                        ) && (l35 == l26)\n                      ) && ((bool21 && (l19 == coll1.getOrElse(placeholder[Int](76), tuple2)._2)) || (!bool21))\n                    ) && (coll37 == coll29)\n                  ) && (l38 == l44)\n                ) && (OUTPUTS(placeholder[Int](77)).propositionBytes == coll39)\n              ) && (OUTPUTS(placeholder[Int](78)).value >= max(placeholder[Long](79), l58))\n            ) && (OUTPUTS(placeholder[Int](80)).propositionBytes == coll33)\n          ) && (OUTPUTS(placeholder[Int](81)).value >= max(placeholder[Long](82), l58 * coll13(placeholder[Int](83)) / placeholder[Long](84)))\n        )} else { placeholder[Boolean](85) }\n      ) || if (((bool42 && (INPUTS.size == placeholder[Int](86))) && (OUTPUTS.size == placeholder[Int](87))) && (\n        CONTEXT.dataInputs.size == placeholder[Int](88)\n      )) {(\n        val l43 = if (bool21) { l20 - l25 } else { l26 - l35 }\n        val box44 = OUTPUTS(placeholder[Int](89))\n        val l45 = if (bool21) { l43 / l23 } else { l43 / l27 }\n        val tuple46 = box44.tokens.getOrElse(placeholder[Int](90), tuple2)\n        (\n          (bool32 && (l25 == l20)) && (\n            (((bool21 && (coll37 == coll30)) && (l38 == l43)) && (box44.value >= l45 * l27 * l22)) || (\n              (((!bool21) && (box12.value >= l43)) && (tuple46._1 == coll30)) && (tuple46._2 == l45)\n            )\n          )\n        ) && (box44.propositionBytes == coll39)\n      )} else { placeholder[Boolean](91) }\n    ) || if (bool41 && (!bool42)) {\n      ((coll10 == coll39) && ((bool21 && (coll28 == coll30)) && (l25 == l20))) || ((!bool21) && (l35 >= l26 - placeholder[Long](92)))\n    } else { placeholder[Boolean](93) }\n  )\n}",
  "address": "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",
  "assets": [
    {
      "tokenId": "777777e5051f8a6bc30827ee41dd39e04bca1dba35236b9a26b494e0bac84f33",
      "index": 0,
      "amount": 1001,
      "name": "fakeUSD",
      "decimals": 2,
      "type": "EIP-004"
    }
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  "additionalRegisters": {
    "R5": {
      "serializedValue": "0e240008cd039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6",
      "sigmaType": "Coll[SByte]",
      "renderedValue": "0008cd039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6"
    },
    "R6": {
      "serializedValue": "0e0130",
      "sigmaType": "Coll[SByte]",
      "renderedValue": "30"
    },
    "R8": {
      "serializedValue": "110a0002028090e4f5f061e807e807d804beeacdfe080a80897a",
      "sigmaType": "Coll[SLong]",
      "renderedValue": "[0,1,1,1681603200000,500,500,300,1206499999,5,1000000]"
    },
    "R7": {
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      "sigmaType": null,
      "renderedValue": null
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    "R9": {
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      "sigmaType": "SSigmaProp",
      "renderedValue": "02042a3559387831c22aaec64a86969b6f2e4b7626b3f94cbec08123c5dc88d23e"
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    "R4": {
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      "sigmaType": "Coll[SByte]",
      "renderedValue": "43616c6c5f415f66616b655553445f4552475f313230363439393939395f323032332d30342d31365f7065725f31"
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  "spentTransactionId": "df2a5aaea09b1b9da7d7c44ddda7fa813b5c6780ceb9bfb09c8970a86e169e8b",
  "mainChain": true
}