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Transaction

5/9/2024 06:10:34 PM
ID: 473f121961...cc1a
Inputs (1)
#0
c229c4fd532b...3efe
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
ce137e27c4b8...8c6c
Settlement height:
1,258,688
Value:
1.43 ERG
Tokens:
Loading assets...
Outputs (14)
#0
33c83c2475c0...ce6c
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
5e52afd212c8...a42c
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#1
7ab4c1b25179...9226
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
7593edb970e3...bce8
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#2
ffa136e76f58...a8dd
Spent
Address:
Auction House (quE2)
Spent in transaction:
4dbb8ebf75f8...0192
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#3
2f2edb4eba4f...ca08
Spent
Address:
Auction House (quE2)
Spent in transaction:
fcf5977be774...4b4f
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#4
25a684eedd64...86aa
Spent
Address:
Auction House (quE2)
Spent in transaction:
c9c5993e8e20...0821
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#5
39e6ec363170...7c8a
Spent
Address:
Auction House (quE2)
Spent in transaction:
00fca8aed8d9...8a59
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#6
45c6a3181c9b...c29f
Spent
Address:
Auction House (quE2)
Spent in transaction:
f01285e0e574...1538
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#7
5a3cee266e1f...80bf
Spent
Address:
Auction House (quE2)
Spent in transaction:
dcde81117d1b...86b0
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#8
82d85bc0c73d...9c34
Spent
Address:
Auction House (quE2)
Spent in transaction:
3edf8e398e9b...5060
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#9
c5da302ac648...7939
Spent
Address:
Auction House (quE2)
Spent in transaction:
b04005a95546...7016
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#10
da49d2bfead6...5ee5
Spent
Address:
Auction House (quE2)
Spent in transaction:
1bc4972fd3be...544f
Settlement height:
1,260,847
Value:
0.015 ERG
Tokens:
Loading assets...
#11
cf5d016d9562...420e
Spent
Address:
9fDB8QW4AgFJ...EECh
Spent in transaction:
568ed31b1443...7cdb
Settlement height:
1,260,847
Value:
1.25 ERG
Tokens:
Loading assets...
#12
51f8b90f9d9e...f296
Spent
Address:
9gjghouPwq9T...Azvo
Spent in transaction:
257afe78e059...c560
Settlement height:
1,260,847
Value:
0.005 ERG
Tokens:
AHT
1,868.79
#13
24f488696de9...fffc
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
5cf26e736419...c3e6
Settlement height:
1,260,847
Value:
0.005 ERG
Transaction Details
Status: Confirmed
Size: 13.2 KB
Received time: 5/9/2024 06:10:34 PM
Included in blocks: 1,260,847
Confirmations: 505,844
Total coins transferred: 1.43 ERG
Fees: 0.005 ERG
Fees per byte: 0.00000037 ERG
Raw Transaction Data
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  "inclusionHeight": 1260847,
  "timestamp": 1715278234023,
  "index": 1,
  "globalIndex": 7172183,
  "numConfirmations": 505844,
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      "spendingProof": "d46f3e9eedd4d89f3b72c64e14c37abf01faaed365e49d0d2a3d60d7754f93122bcae53aa8f532740ea3e4df50f94c2778938eacc987fa8c",
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      "ergoTreeConstants": "",
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          "sigmaType": "SLong",
          "renderedValue": "100000000"
        },
        "R7": {
          "serializedValue": "110280dddb0180fca402",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1800000,2400000]"
        },
        "R4": {
          "serializedValue": "043c",
          "sigmaType": "SInt",
          "renderedValue": "30"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "33c83c2475c0c233dd153275d1f69d76be92831247867f5b9f5396fe6dc3ce6c",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 0,
      "globalIndex": 39942147,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 0\n48: 1\n49: 0\n50: 1\n51: 0\n52: 1\n53: 0\n54: 0\n55: 0\n56: 1\n57: 0\n58: 1\n59: 2\n60: 0\n61: false\n62: 0\n63: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val coll2 = Coll[Byte]()\n  val l3 = SELF.value\n  val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n  val l5 = tuple4._2\n  val opt6 = SELF.R6[Coll[Long]]\n  val coll7 = opt6.get\n  val l8 = coll7(placeholder[Int](1))\n  val coll9 = SELF.R7[Coll[Byte]].get\n  val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n  val bool11 = l10 < l8\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val l13 = CONTEXT.preHeader.timestamp\n  val tuple14 = SELF.R5[(Long, Long)].get\n  val l15 = tuple14._1\n  val l16 = tuple14._2\n  val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n  val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n  val i19 = box18.R4[Int].get\n  val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll21 = box20.tokens\n  val l22 = box20.value\n  val tuple23 = (coll2, l22)\n  val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n  val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n  val coll26 = box25.tokens\n  val l27 = box25.value\n  val tuple28 = (coll2, l27)\n  val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n  val coll30 = SELF.R8[Coll[Byte]].get\n  val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n  sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n        val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n        val i33 = OUTPUTS.size\n        val box34 = OUTPUTS(placeholder[Int](13))\n        val l35 = placeholder[Long](14) * box18.R6[Long].get\n        val box36 = box20\n        val coll37 = coll21\n        val l38 = l22\n        val tuple39 = tuple23\n        val tuple40 = tuple24\n        val box41 = box25\n        val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n        val opt43 = box42.R4[Int]\n        val bool44 = opt43.isDefined\n        val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n          val i45 = opt43.getOrElse(placeholder[Int](17))\n          if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n        )} else { placeholder[Int](23) }\n        val coll46 = coll26\n        val l47 = l27\n        val tuple48 = tuple28\n        val tuple49 = tuple29\n        val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n        val tuple51 = coll1(placeholder[Int](25))\n        ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n                val i52 = opt43.getOrElse(placeholder[Int](32))\n                if ((i52 < placeholder[Int](33)) || (i52 >= placeholder[Int](34))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](36), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](37)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](38)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                    val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                    val i54 = coll53.size\n                    coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i54) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](43), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](44)) }\n                      })\n                  )} else { placeholder[Boolean](45) } }\n              )} else { placeholder[Boolean](46) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](47))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](48), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](49)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](50))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](51), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](52)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](53)) == coll33(placeholder[Int](54)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n              val tuple40 = box32.R5[(Long, Long)].get\n              (tuple40._1 == l15) && (tuple40._2 <= l13)\n            )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](55))) { l16 + coll37(placeholder[Int](56)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](57)) { placeholder[Int](58) } else { placeholder[Int](59) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](60))))\n      )} } else { placeholder[Boolean](61) }) && sigmaProp(box18.tokens(placeholder[Int](62))._1 == placeholder[Coll[Byte]](63))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "c390c0eaa4ad2852c06c78fa6271a9a7d8f088bb48aeb07b186521eace541acc",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #1 mhs sam",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980d385a6ec638093dbe28d64",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342456000,1719835256000]"
        },
        "R6": {
          "serializedValue": "110380d0dbc3f40280c8afa02580a0b787e905",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[50000000000,5000000000,100000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "5e52afd212c855a1bc3b9835c758ec5e4b7102087447d0e334ad62b5b704a42c",
      "mainChain": true
    },
    {
      "boxId": "7ab4c1b251795aa8a0b6fb5f680c3182aedd1d5a84d070d9854b53170f999226",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 1,
      "globalIndex": 39942148,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 0\n48: 1\n49: 0\n50: 1\n51: 0\n52: 1\n53: 0\n54: 0\n55: 0\n56: 1\n57: 0\n58: 1\n59: 2\n60: 0\n61: false\n62: 0\n63: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val coll2 = Coll[Byte]()\n  val l3 = SELF.value\n  val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n  val l5 = tuple4._2\n  val opt6 = SELF.R6[Coll[Long]]\n  val coll7 = opt6.get\n  val l8 = coll7(placeholder[Int](1))\n  val coll9 = SELF.R7[Coll[Byte]].get\n  val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n  val bool11 = l10 < l8\n  val coll12 = SELF.R4[Coll[Byte]].get\n  val l13 = CONTEXT.preHeader.timestamp\n  val tuple14 = SELF.R5[(Long, Long)].get\n  val l15 = tuple14._1\n  val l16 = tuple14._2\n  val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n  val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n  val i19 = box18.R4[Int].get\n  val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll21 = box20.tokens\n  val l22 = box20.value\n  val tuple23 = (coll2, l22)\n  val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n  val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n  val coll26 = box25.tokens\n  val l27 = box25.value\n  val tuple28 = (coll2, l27)\n  val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n  val coll30 = SELF.R8[Coll[Byte]].get\n  val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n  sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n        val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n        val i33 = OUTPUTS.size\n        val box34 = OUTPUTS(placeholder[Int](13))\n        val l35 = placeholder[Long](14) * box18.R6[Long].get\n        val box36 = box20\n        val coll37 = coll21\n        val l38 = l22\n        val tuple39 = tuple23\n        val tuple40 = tuple24\n        val box41 = box25\n        val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n        val opt43 = box42.R4[Int]\n        val bool44 = opt43.isDefined\n        val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n          val i45 = opt43.getOrElse(placeholder[Int](17))\n          if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n        )} else { placeholder[Int](23) }\n        val coll46 = coll26\n        val l47 = l27\n        val tuple48 = tuple28\n        val tuple49 = tuple29\n        val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n        val tuple51 = coll1(placeholder[Int](25))\n        ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n                val i52 = opt43.getOrElse(placeholder[Int](32))\n                if ((i52 < placeholder[Int](33)) || (i52 >= placeholder[Int](34))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](36), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](37)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](38)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                    val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                    val i54 = coll53.size\n                    coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i54) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](43), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](44)) }\n                      })\n                  )} else { placeholder[Boolean](45) } }\n              )} else { placeholder[Boolean](46) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](47))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](48), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](49)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](50))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](51), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](52)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](53)) == coll33(placeholder[Int](54)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n              val tuple40 = box32.R5[(Long, Long)].get\n              (tuple40._1 == l15) && (tuple40._2 <= l13)\n            )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](55))) { l16 + coll37(placeholder[Int](56)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](57)) { placeholder[Int](58) } else { placeholder[Int](59) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](60))))\n      )} } else { placeholder[Boolean](61) }) && sigmaProp(box18.tokens(placeholder[Int](62))._1 == placeholder[Coll[Byte]](63))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "83eebb894287d2c47e28ab190d5b18fd03421605d5acfac9a47e2c65dc97c7f8",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #2 joseph",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980e8fea5ec6380a8d4e28d64",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342400000,1719835200000]"
        },
        "R6": {
          "serializedValue": "110380d0dbc3f40280c8afa02580a0b787e905",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[50000000000,5000000000,100000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "7593edb970e3d5baa9516dd4c428a18699f0b9d10408d26ae0ea4396e099bce8",
      "mainChain": true
    },
    {
      "boxId": "ffa136e76f58faeb70fbcf8f57d238bd10b1340c61b8d5dec111bb74f3eaa8dd",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 2,
      "globalIndex": 39942149,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "146197582c6bf19a0e7e8be27af773b80f0426495f0b65efff8579efd342ee52",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #3 fateme",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R5": {
          "serializedValue": "59c0a6ffa5ec63c082c4c28365",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
        },
        "R6": {
          "serializedValue": "110380b09dc2df010002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[30000000000,0,1]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        }
      },
      "spentTransactionId": "4dbb8ebf75f82a44bf90bd2fd19cdad4395ba4039953eec5d1200085736b0192",
      "mainChain": true
    },
    {
      "boxId": "2f2edb4eba4f60929767fa6464a17a0a0d7480d1b4785dbea03278a0c787ca08",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 3,
      "globalIndex": 39942150,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "102c04000400040404020404040004020400040604000406050404020400040004d00f040004040414040404000400040005d00f05d00f04000400040404140406040005d00f040405d00f0400040604060400050001000101010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed814d601e4c6a7040ed602db6903db6503fed603e4c6a70559d6048c720301d605b2db6501fe730000d606e4c672050404d607e4c6a70611d60899b272077301009c9d9972027204b27207730200b27207730300d609b2a5730401a7d60adb63087209d60b830002d60cc17209d60d8602720b720cd60eb2720a730501720dd60fe4c6a7070ed610b2a5730601a7d611db63087210d612c17210d6138602720b7212d614b272117307017213ea02eb02cdeeb472017308b17201d1959172027204959172028c720302d801d615b2a57309009683040193b1a5730a93db63087215db6308a792c1721599c1a79c730be4c67205060593c272157201d80fd6157209d616720ad617720bd618720cd619720dd61a720ed61b7210d61ce5c6721b0463b2a599b1a5730c00d61dc6721c0404d61ee6721dd61f7211d6207212d6217213d6227214d623b2db6308a7730d009683050193c5b2a4730e00c5a7eded93c272157201928c721a029d9c72087e9999730f720695721ed801d624e5721d731095ec8f722473119272247312722495ed9372247313e6c6721c050c4c0eb0e5c6721c050c4c0e83004c0e7314d90125404c0e9a8c7225018c8c7225020273157316057317938c721a01720feded93c2721be4c67205050e928c7222029d9c72087e7206057318938c722201720f937223b2db6308b2a5731901a7731a00ed95721ed801d624e4721d95ec8f7224731b927224731cd802d625b2a5731d01a7d626b2db63087225731e0186027217c17225eded928c7226029d9c72087e722405731f938c722601720f93c27225c2721c95ed9372247320e6c6721c050c4c0ed802d625e5c6721c050c4c0e83004c0ed626b1722593b4ad7225d901274c0e86028c7227019d9c7e8c722702057208732173227226adb4a573239a73247226d9012763d801d629b2db6308722773250186027217c1722795938c722901720f8602c272278c7229028602721773267327732893cbc3721c8c7223017329d1938cb2db63087205732a0001732b",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "b48d018ae0ada5d204dac9f3ad2a616ad74e029f5adfbd369c819e6e3b1fc43b",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #4 mohammad",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R5": {
          "serializedValue": "59c0a6ffa5ec63c082c4c28365",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
        },
        "R6": {
          "serializedValue": "110380b09dc2df010002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[30000000000,0,1]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        }
      },
      "spentTransactionId": "fcf5977be7744607b686750a9e6219efb537e3a845a05c47bc2bdd83cc494b4f",
      "mainChain": true
    },
    {
      "boxId": "25a684eedd64b46652cb607232206a1e3afedec1441b58bea58304fdb4b586aa",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 4,
      "globalIndex": 39942151,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "876e31aeaab0c915e8545c11410bdc25168e547649b7d8648c74d4a8a5ecbe29",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #5 moein",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R5": {
          "serializedValue": "59c0a6ffa5ec63c082c4c28365",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
        },
        "R6": {
          "serializedValue": "110380b09dc2df010002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[30000000000,0,1]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        }
      },
      "spentTransactionId": "c9c5993e8e2070136ca073c03cf508366ffdd936121bd5bbe448316e69fc0821",
      "mainChain": true
    },
    {
      "boxId": "39e6ec36317087951f22685bf8373fdab21689d2f4cdfa55d1321b7f2cf07c8a",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 5,
      "globalIndex": 39942152,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "0ac7c4e061a4390dc74599e43ba8d64ebdd3ab038f24a9cf7420020df0609fee",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #6 radni",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R5": {
          "serializedValue": "59c0a6ffa5ec63c082c4c28365",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
        },
        "R6": {
          "serializedValue": "110380b09dc2df010002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[30000000000,0,1]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        }
      },
      "spentTransactionId": "00fca8aed8d981f1254595bb0714f2c7861a1c8d6b84d33e157157e352a78a59",
      "mainChain": true
    },
    {
      "boxId": "45c6a3181c9b6dce07a9ce1ef932cccbfc1ed81b77c158b30effb1602a02c29f",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 6,
      "globalIndex": 39942153,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
      "address": "quE2HvwgAp7z8q4tD1BfCfj72TPziUHqruk3L8jUWQ7bWGD7ugdkpkgYx9kztPTmJborN4baTrHuenaZrCtoB3VHeLjQUQACzZ67qpnMGUAyGs93mUpwodKekvSM8Y6rCFVMxFw76MD8ZUjMPd2J8awcfECurL9v6HkjFnzKJr72NXdQ18XYYGRneXbbkgU5qzUKTLoC2weUGsDpNhfDh9xBGV7CYconikP79c9b3ZcquSBdNCu4G5r2uvBVTHXaFgk5TioeSL4SqwS5sugeEeicTPre842uZBzNd7B3XqE75Rjum1bz1vBgGtadMqt2XRui7tqaK44LjeYfds3N4CWZsYwx69h2PpHFrU9Mzvvj3ju6XGVS5X6GnyGgttXiHgokZPhD45m2etzAUXovNPeutrw5zmQudCh9jXBSfujXDBPS7ohC7qLj3Hj4zfRJTmUzPNMEUGLED57kowMXdAq95h4LciSLcNgZjM3dAwVkkPFgTnu1gvFSR6HAb78d8cx4khpf5bvtPpRxLk1vXeqRxBagUQwgaTBJUEAbxF9bfs7TQBzboKL5krjpqXKydYQb5pbZ64bRk6U6hzNjmn8XEexRE8RACaJrk9MvtXVVqJRyKRkWRvMKgo3QtfXR1qNZcXKV5AHzwCPfHXfxXAkSkEPPXFxYyj33KLuuLAw7LyWqL1v6fFXzohq1oZB3tqXGZbksri3i86cCtMoUFUCUHT2BgCxUmQVGnuUvNTe69PU5VKraGowqUo8MJFXS7njsW7uZyK867qZpPPXwu2fLgK2whDihx6JKY1Ub3aw3mUkjbdqhMxSh4m6ZhD2piJYwtiEb7juZhrhVWVqaJDFCc2aED8Vdc1Z4W9pEt8UKhHcLcHn6CiaSHiyhFwRY3bMuVZwtY2XFwzQRSfW2VyYoC5Dqby43xYuEHe1Ld7ANMsXgHzwwkisdt4rQ1EHMynXM6926DEVYewgxrGEaXdYDymLWZ5DKHdmyvYW6keH9NysQGKytiax8wUyiqyaLhXoqbJCWxrcyu9MZLZpJFRXonKCNK1SAmRkRNQfkmY9jDVnj5nBdjtEGxa9pwAFENv6xa58J1zcA4MD6Tj9B4B36YrWT2TLs7Pp4jMJryA5sUVsL6jn7cEnbjaH78qQw2sicncneBaAoQnFJedyWfnQC3GYRAfRPp3kxfZNsJf2aQQ",
      "assets": [
        {
          "tokenId": "5459f49ef792835a3b7639e4da2d74b232f8f1c144a8488fe0e591f706218bfc",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #7 raactor",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R5": {
          "serializedValue": "59c0a6ffa5ec63c082c4c28365",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
        },
        "R6": {
          "serializedValue": "110380b09dc2df010002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[30000000000,0,1]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        }
      },
      "spentTransactionId": "f01285e0e574b366354668e27838f0260c7867b103f3f63a643173f9a1b81538",
      "mainChain": true
    },
    {
      "boxId": "5a3cee266e1f72d3cd76b8e7f1e26f9d5fde6522ff838756666a67811f6f80bf",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 7,
      "globalIndex": 39942154,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "66f1ea303b5b64c57829406c7f3368ecbc8b094386c8ce49c6dade0a6b522a01",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #8 vorujack",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R5": {
          "serializedValue": "59c0a6ffa5ec63c082c4c28365",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
        },
        "R6": {
          "serializedValue": "110380b09dc2df010002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[30000000000,0,1]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        }
      },
      "spentTransactionId": "dcde81117d1bf54c25c00da564722bd193467662deef077a59d16c9909db86b0",
      "mainChain": true
    },
    {
      "boxId": "82d85bc0c73d97d48dee8cec28adf576a0e6f7d82fcdcd87bc726f70de3b9c34",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 8,
      "globalIndex": 39942155,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "0fa9f530b19e7a9dd7a156ec389c32b9778f30af114b18e8c5b92e80ab37c494",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #9 cw",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R5": {
          "serializedValue": "59c0a6ffa5ec63c082c4c28365",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
        },
        "R6": {
          "serializedValue": "110380b09dc2df010002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[30000000000,0,1]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        }
      },
      "spentTransactionId": "3edf8e398e9b0d6bae5eda4abc543ba447cd3297673122517e208509c9625060",
      "mainChain": true
    },
    {
      "boxId": "c5da302ac6488f020ab4dbc08c97f9758726ffb4897dc1e0bbfbdfff6c907939",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 9,
      "globalIndex": 39942156,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "c7a076bc69157776dca15975c97a8dea3862b80be57ca6837641f0096dbbb384",
          "index": 0,
          "amount": 1,
          "name": "ergo watcher #10 qx",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R5": {
          "serializedValue": "59c0a6ffa5ec63c082c4c28365",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
        },
        "R6": {
          "serializedValue": "110380b09dc2df010002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[30000000000,0,1]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        }
      },
      "spentTransactionId": "b04005a95546b7fbaf0a4816e0cc09ccf371f7cec9537cb6b9d30e3cece67016",
      "mainChain": true
    },
    {
      "boxId": "da49d2bfead64215449fd3bd08db32c5fbe4e03fa26bf2d187ce5ed311135ee5",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 15000000,
      "index": 10,
      "globalIndex": 39942157,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll10 = box9.tokens\n  val coll11 = Coll[Byte]()\n  val l12 = box9.value\n  val tuple13 = (coll11, l12)\n  val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n  val coll15 = SELF.R7[Coll[Byte]].get\n  val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll17 = box16.tokens\n  val l18 = box16.value\n  val tuple19 = (coll11, l18)\n  val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box21 = OUTPUTS(placeholder[Int](9))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n      )} else {(\n        val box21 = box9\n        val coll22 = coll10\n        val coll23 = coll11\n        val l24 = l12\n        val tuple25 = tuple13\n        val tuple26 = tuple14\n        val box27 = box16\n        val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n        val opt29 = box28.R4[Int]\n        val bool30 = opt29.isDefined\n        val coll31 = coll17\n        val l32 = l18\n        val tuple33 = tuple19\n        val tuple34 = tuple20\n        val tuple35 = SELF.tokens(placeholder[Int](13))\n        allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n                  val i36 = opt29.getOrElse(placeholder[Int](16))\n                  if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n                )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n              val i36 = opt29.get\n              if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n                val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n                val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n                ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n              )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                  val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                  val i38 = coll37.size\n                  coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n                      val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n                      if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n                    })\n                )} else { placeholder[Boolean](39) } }\n            )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n      )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
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          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1715342404000,1735639204000]"
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          "sigmaType": "Coll[SByte]",
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      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(240e71,dfb102,...)))}",
      "address": "9gjghouPwq9TCKyFAAvHPsoE1n9moZWec9oKeRzAjnV9p4hAzvo",
      "assets": [
        {
          "tokenId": "18c938e1924fc3eadc266e75ec02d81fe73b56e4e9f4e268dffffcb30387c42d",
          "index": 0,
          "amount": 18687911,
          "name": "AHT",
          "decimals": 4,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "257afe78e059e55be46c9fc029910a525f83891e1bf0bf782e3c3267a46ac560",
      "mainChain": true
    },
    {
      "boxId": "24f488696de963a4892ca74f635fbb86ca04288ac1a2d75f50c5271d3599fffc",
      "transactionId": "473f121961c7ac4a8a39e4e348dd96b6febdebc27473f09b53a0a66f5c95cc1a",
      "blockId": "bc375b5bb7a4e7d873d9c436bf3ccdc2922ec26747138c614150103486ebfc7b",
      "value": 5000000,
      "index": 13,
      "globalIndex": 39942160,
      "creationHeight": 1260845,
      "settlementHeight": 1260847,
      "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": "5cf26e73641903cc226f4298f13eac47471958dc84f0e0ab7cb9f14bdc37c3e6",
      "mainChain": true
    }
  ],
  "size": 13520,
  "isUnconfirmed": false
}