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Transaction

4/18/2024 08:48:11 AM
ID: c67635f794...857f
Inputs (10)
#0
fbbac828b610...748b
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
bb5a307fa2f2...8953
Settlement height:
1,244,982
Value:
0.005 ERG
Tokens:
Loading assets...
#1
c2e69f917b8e...0e09
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
60011050302b...1db0
Settlement height:
1,244,982
Value:
0.005 ERG
Tokens:
Loading assets...
#2
8826a863d4f3...c07c
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
c038af8806a0...4d8f
Settlement height:
1,244,982
Value:
0.005 ERG
Tokens:
Loading assets...
#3
0a4a7251b77b...3790
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
5295addd2985...2046
Settlement height:
1,244,982
Value:
0.005 ERG
Tokens:
Loading assets...
#4
e6bf50c4383b...c99f
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
51f366884d4d...9028
Settlement height:
1,244,162
Value:
0.005 ERG
Tokens:
Loading assets...
#5
efb4c823cf53...f5be
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
edf441765b4c...f9b7
Settlement height:
1,245,530
Value:
0.083 ERG
Tokens:
Loading assets...
#6
c940519fcdbb...a6be
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
ee458961e233...20c2
Settlement height:
1,244,162
Value:
0.005 ERG
Tokens:
Loading assets...
#7
b2712315dfa0...7623
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
8b7e590c3cb3...a4ef
Settlement height:
1,244,162
Value:
0.005 ERG
Tokens:
Loading assets...
#8
53c37f685e58...3ce9
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
b78eb3201155...e914
Settlement height:
1,245,523
Value:
0.073 ERG
Tokens:
Loading assets...
#9
b207cf17c064...c9a1
Spent
Address:
9fDB8QW4AgFJ...EECh
Output transaction:
3af7ba9edfc7...2180
Settlement height:
1,245,178
Value:
0.582037969 ERG
Tokens:
Loading assets...
Outputs (12)
#0
5bfef423c176...dead
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
378cd83df5a2...d367
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#1
bbcb7b43320a...b960
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
68a9f424a34e...4296
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#2
6c9ea5d53ab0...3668
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
51a2a6a8dfeb...bd08
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#3
b6762e6d104f...ee8f
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
e8457b990a76...9930
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#4
c1c37275bd67...4ce6
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
df421b6ea8ae...f200
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#5
1dc4fbaae477...29c8
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
de308c2abc1c...9b9c
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#6
58c3ffe6257d...e64a
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
fe3ec7af5e1d...962b
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#7
f6b602c75795...5b73
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
ad74b6234413...cfc6
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#8
c2d2a459d534...1cb7
Spent
Address:
GZJ5yvPXrP52...qatt
Spent in transaction:
42c2a553f39e...82b6
Settlement height:
1,245,546
Value:
0.015 ERG
Tokens:
Loading assets...
#9
191aa4a87a1a...d569
Spent
Address:
9fDB8QW4AgFJ...EECh
Spent in transaction:
ee3b6c52ce90...946a
Settlement height:
1,245,546
Value:
0.628037969 ERG
Tokens:
Loading assets...
#10
b0c301af49a2...328e
Spent
Address:
9gjghouPwq9T...Azvo
Spent in transaction:
343fcbef7166...08bc
Settlement height:
1,245,546
Value:
0.005 ERG
Tokens:
AHT
1,862.12
#11
29b24603bb8d...deff
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
97fd32cdd127...ae9c
Settlement height:
1,245,546
Value:
0.005 ERG
Transaction Details
Status: Confirmed
Size: 14.21 KB
Received time: 4/18/2024 08:48:11 AM
Included in blocks: 1,245,546
Confirmations: 521,204
Total coins transferred: 0.773037969 ERG
Fees: 0.005 ERG
Fees per byte: 0.000000344 ERG
Raw Transaction Data
{
  "id": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
  "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
  "inclusionHeight": 1245546,
  "timestamp": 1713430091939,
  "index": 2,
  "globalIndex": 7038236,
  "numConfirmations": 521204,
  "inputs": [
    {
      "boxId": "fbbac828b6101ea719657098c3931a2d97d08cda662312dc3f1e7ce73457748b",
      "value": 5000000,
      "index": 0,
      "spendingProof": "61952118986a3758fa73a0ce448c2fee8c460ec73b2814ca7c409b8726a2b2032f13f95b81285652cbcee1dd6b0bc35195baf54f8cae86cb",
      "outputBlockId": "52a6374af1585757f523998631f9ca7630b7d9df34c584bed6265aa43c714f44",
      "outputTransactionId": "bb5a307fa2f2510c0f7aa32eb1cc69392b4d54917eb76216b0e68d1eb9398953",
      "outputIndex": 0,
      "outputGlobalIndex": 39276376,
      "outputCreatedAt": 1244980,
      "outputSettledAt": 1244982,
      "ergoTree": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(5b1574,267d10,...)))}",
      "address": "9fDB8QW4AgFJvRjfesjAKU5bLRjAohe5BGXgnwfHAAeccKyEECh",
      "assets": [
        {
          "tokenId": "ffcfb0abd8caa65a7d40c9072b500da1014241c4ab37974c944f7812f628585e",
          "index": 0,
          "amount": 1,
          "name": "Demetrius",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
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        "R6": {
          "serializedValue": "0400",
          "sigmaType": "SInt",
          "renderedValue": "0"
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        "R8": {
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          "sigmaType": "Coll[SByte]",
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        "R7": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "0101"
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        "R4": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "44656d657472697573"
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    },
    {
      "boxId": "c2e69f917b8ee284d798f2d2c18ae940b48475708b6304b76865fbbe12250e09",
      "value": 5000000,
      "index": 1,
      "spendingProof": "d5279930e93f7015ec4dbaddd4a5b4d6bb62067d3c54aa3d0966cced40c52d314ec63e369e1f012e396b2b8225e41713e7e11473cbfc7d85",
      "outputBlockId": "52a6374af1585757f523998631f9ca7630b7d9df34c584bed6265aa43c714f44",
      "outputTransactionId": "60011050302b70d4dbf057ce7ec5ed36088ab1db0fa4c0ea582caf519cc91db0",
      "outputIndex": 0,
      "outputGlobalIndex": 39276404,
      "outputCreatedAt": 1244980,
      "outputSettledAt": 1244982,
      "ergoTree": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(5b1574,267d10,...)))}",
      "address": "9fDB8QW4AgFJvRjfesjAKU5bLRjAohe5BGXgnwfHAAeccKyEECh",
      "assets": [
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          "index": 0,
          "amount": 1,
          "name": "Odysseus",
          "decimals": 0,
          "type": "EIP-004"
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        },
        "R6": {
          "serializedValue": "0400",
          "sigmaType": "SInt",
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        "R7": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "4f64797373657573"
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          "renderedValue": "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"
        },
        "R6": {
          "serializedValue": "0400",
          "sigmaType": "SInt",
          "renderedValue": "0"
        },
        "R8": {
          "serializedValue": "0e200623904ec0b26767a1c9548fc30f7ffb83fb6618048e89a7934130877feaa33a",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0623904ec0b26767a1c9548fc30f7ffb83fb6618048e89a7934130877feaa33a"
        },
        "R7": {
          "serializedValue": "0e020101",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0101"
        },
        "R9": {
          "serializedValue": "0e42697066733a2f2f626166796265696271336c7374357367327075626b78346375733568613464636f696f333278626d796c6333686471706f766c6868717278766c75",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "697066733a2f2f626166796265696271336c7374357367327075626b78346375733568613464636f696f333278626d796c6333686471706f766c6868717278766c75"
        },
        "R4": {
          "serializedValue": "0e0641706f6c6c6f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "41706f6c6c6f"
        }
      }
    },
    {
      "boxId": "53c37f685e582be0abb51426fef3ab0ae2b397ff519fe00de40b78eed2563ce9",
      "value": 73000000,
      "index": 8,
      "spendingProof": "3a18cc8d19181f60363edcfe545a17d1c7ea9cd19a880b1c28406a1372424db7b0e89098998697f253fade780f5dcddb2e162375af5fdd4a",
      "outputBlockId": "636b0156c3be6c997740096d71aecfa9331a625eac5b610f4f847dc8846faa60",
      "outputTransactionId": "b78eb32011556f1b5f5536c6ae64e095baeb50d4d559b205816180057b83e914",
      "outputIndex": 2,
      "outputGlobalIndex": 39301907,
      "outputCreatedAt": 1245521,
      "outputSettledAt": 1245523,
      "ergoTree": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(5b1574,267d10,...)))}",
      "address": "9fDB8QW4AgFJvRjfesjAKU5bLRjAohe5BGXgnwfHAAeccKyEECh",
      "assets": [
        {
          "tokenId": "b5a37518959c5d00455562f718502dfbfabd707b3499fee42e360712304d8a59",
          "index": 0,
          "amount": 1,
          "name": "Aeschylus",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "b207cf17c064e8067b7218455b9a4bb841e34858ec5081b2655dcd215650c9a1",
      "value": 582037969,
      "index": 9,
      "spendingProof": "aad63eac37d4dd8401d107ad7b7cab40f056ee72625ef4e4b6d4ba3bfb25fdb339f1eecb18790706df0ead8d174860e99602d9d90eb55141",
      "outputBlockId": "3dc9d495562335d5925bca4dd8ea0100c3c99110a5293427768ef2140fddd361",
      "outputTransactionId": "3af7ba9edfc72a5c5ef5a657c3dc1ea27823ef614055daf86d69a2eab1062180",
      "outputIndex": 2,
      "outputGlobalIndex": 39285422,
      "outputCreatedAt": 1245175,
      "outputSettledAt": 1245178,
      "ergoTree": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(5b1574,267d10,...)))}",
      "address": "9fDB8QW4AgFJvRjfesjAKU5bLRjAohe5BGXgnwfHAAeccKyEECh",
      "assets": [
        {
          "tokenId": "f0d5bdf474fcbd4249608e6dc6e9cf34a327b218f66445ea545b4c711b4676e3",
          "index": 0,
          "amount": 1234321,
          "name": "COS",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "ebb40ecab7bb7d2a935024100806db04f44c62c33ae9756cf6fc4cb6b9aa2d12",
          "index": 1,
          "amount": 21069420,
          "name": "🚬",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "0779ec04f2fae64e87418a1ad917639d4668f78484f45df962b0dec14a2591d2",
          "index": 2,
          "amount": 2000,
          "name": "Mi Goreng ",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "6ad70cdbf928a2bdd397041a36a5c2490a35beb4d20eabb5666f004b103c7189",
          "index": 3,
          "amount": 69420,
          "name": "rsHOSKY",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "18c938e1924fc3eadc266e75ec02d81fe73b56e4e9f4e268dffffcb30387c42d",
          "index": 4,
          "amount": 37806150,
          "name": "AHT",
          "decimals": 4,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [
    {
      "boxId": "dc5baed8d08ae04cc52d24d6947963d70ed36721da7480180a16bcbf30882908",
      "value": 3219364,
      "index": 0,
      "outputBlockId": "0926ca09654a5cc52df11736853080d7f207e81e4f447657c7c26f2c2023f2b2",
      "outputTransactionId": "a3c9f6e7ba3ef05707139ee011a82bd134591edff86f40ef6e2313e1c9c280ca",
      "outputIndex": 0,
      "ergoTree": "0008cd03b04048a9708f0a2b109d75513a2483e3b9ede622efb3cc03bdddf93bccd93ac5",
      "address": "9hoRnjysKfkwZSCgSFNzSXMohwYn8DqruuYxD6vT7Ubw55qnwiZ",
      "assets": [],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "0e240008cd03d4e3f9c9956945986a2bc2621a2fc02b9f7492fe57c87be07a33a0d7ccef5bc8",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03d4e3f9c9956945986a2bc2621a2fc02b9f7492fe57c87be07a33a0d7ccef5bc8"
        },
        "R6": {
          "serializedValue": "0580dac409",
          "sigmaType": "SLong",
          "renderedValue": "10000000"
        },
        "R8": {
          "serializedValue": "058084af5f",
          "sigmaType": "SLong",
          "renderedValue": "100000000"
        },
        "R7": {
          "serializedValue": "110280dddb0180fca402",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1800000,2400000]"
        },
        "R4": {
          "serializedValue": "043c",
          "sigmaType": "SInt",
          "renderedValue": "30"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "5bfef423c17683a14dabc02c54b75fd8003dc05ded351fc59d5fd7f43d14dead",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 0,
      "globalIndex": 39302546,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "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": "GZJ5yvPXrP52Pc7JYv5gt8E5hQbQTgwVm6xiRkWLqh3gdEgsWtHomjmDVCPdFGoscG3YZ5z9yWENPJG3Fnn12KrJ89Zc2gsAa3uBYugxaut69LWsi2UTjjXs9xD7Sf26SvpUmoBBqj1i6duhL76iDSJVihZh7yZiZMLRuSBmiUxsf4S16CVtthYwvZ9Z9LyFGEPXTcWiuTHzG3HhPyji429vfRqyZXXTcEWckAim4k9vU3nZ7Q4dAzqjZDJpgD5QJKP8co7uUJEu4Ef1drk1ha2hPH6ZbC9h2awzbUbCqBVUgPkYZRY5cxHSJGQJw7jAQsd6As2eabaH5iwByu7FKvXbNMiWnqHUPekr6bAdja5gYBnHak4sopo5ihXs1TYufRwp6cxGD1Dt8VWLWJHQKgmSzVmd7CGJfZpVg354Q4YSdK93yxLMUEWdnsatu42UNWbwUGpqsgg3inKDdBYgG6mD2BpmJknMbahrMpaCQhcySZcweySkD7E9Ab5oPPbjV8J3XzoFM344C7iBmXPhYEjenocn21WXFkM1dzQQqRju26zVJFtBdgUxc9DUW9WUTxuE6yu8YLjWNRW5zxXy1zVqsmaVmRa7dSDRg63YrsfrBgFXHSqKongEnXzDnzcHV8qirE7NVEqXT6NpfLDAwB7oxyPx3xwz1b4zy2PbXjG7w5N4MaVYvSG13JRxM5pxEgHF1fwh2SuvGKcF3dZnVEPJDChGFDgc2CmZbn1k4UAcheS7ZvVXBRmiZUcYehE9igQPum22yTvAgtLzkAocvM7yzdPGbm32DVMkiJRKkYEMizQvS3RjtXpUrLSDacRpwc1qxF1DKFbGF8JcdC5peR69mhyQT9r6yiVgLYBWD6t3M5otQ4jDCWUkeLy6zfNwead8VPU1DeTtwZ5neeGR4MwMYZbvvEJSFsZFJDwxEnRxjSzwzkG7SCnLmDUAhjbBXT3fXmoEMB4S7b34qGYk8V9GVhcBEyTYYQStEZxdDsKQUvd14twknkna6xkjFJWU6t18vvdxYpK7PkyJBtrXKyj7R3gesqDmgRaDTnPB47MKaJ3K953uVVefrfFovRQ4fibP6GcH2m6thn2pDvPwTvufXSCAxMpheER65DaSKa3UZnXwKr4hTN7sCPPDYDL3zCoFJBSFK9qoy28jA67Kiet4kbnBjj3c3Z66fC6EXKcS5EDCwNXBSBofR1zoFXdN29yS4dUbjMPygS9v6dnySyP7GiCrxhpi9stkbT7BG317SCP3LEcVBC6kLZwLRtbgsbf61bpcunVvTjEKxvQc66se5k66qfk3fwGMAiP7YypepNFtgfcy6YXQwCUGC8CNreCLh6ae6Q2PapspTAxmMu7m8QMmPMnSiUwr2soea8ui5fn8yMFy4ZnFpnJtvny7Bm2KmYfjC4gwKtg89HJD3KuAQKN83oXiS8h9YSEiYsTzAoXgG8h7ecmb3Z5Y9vxy9T9NGx5CBxsBa8QiwBfdy5C3C6f4pX8eeuWoqAW5HFuVy96vKyQWTVEgJ6jtDgEcRHJkB1uCZdawAXttNbZnj5xF4Ev5X4xe5Lptgr2Vcr2n9WuoDChohbsJSFMP2ucrDAzq1DuDCC1dUH5Vk8pFV9CYeyrgndWwb4XTZAJ1APMtZhLTcRtGJ9piaMEZZEvyK3ZidRWVguAWdGR5Xg3o1SeM95UGwhfJHmNDfnXekcFfy9zBZ8pprWucVUXQsjeCbde1ftEukPmjCVVUc4kCTpe7sq8FVjpixso4ytHcR2fpwMM1nDc8SH1DDtVYC82dfi2n2QX1h3qatt",
      "assets": [
        {
          "tokenId": "ffcfb0abd8caa65a7d40c9072b500da1014241c4ab37974c944f7812f628585e",
          "index": 0,
          "amount": 1,
          "name": "Demetrius",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "110380e888874380a8d6b9078080e59a77",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[9000000000,1000000000,16000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "378cd83df5a24ed5ace706c3e550bfa85c0f91160e988500dc188052a31ad367",
      "mainChain": true
    },
    {
      "boxId": "bbcb7b43320ab48b3c7c2ddeeb70aff5788b1b9a5df8cc52615ec1984d13b960",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 1,
      "globalIndex": 39302547,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "ergoTree": "1040040204000500040405000400040404000402040004000406050004000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f04000400040404140406040005d00f040405d00f040004060406040005000100010104000402050004020400040204000400040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed81fd601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60b8f720a7208d60ce4c6a7040ed60ddb6903db6503fed60ee4c6a70559d60f8c720e01d6108c720e02d611b272077303017304d612b2db6501fe730500d613e4c672120404d614b2a5730601a7d615db63087214d616c17214d617860272027216d618b272157307017217d619b2a5730801a7d61adb63087219d61bc17219d61c86027202721bd61db2721a730901721cd61ee4c6a7080ed61f93c5b2a4730a00c5a7ea02eb02ea02d1720bcdeeb4720c730bb1720cd19591720d720f9591720d7210d814d620ec92720a7208ed917211730c92720a7211d621b1a5d622b2a5730d00d6239c730ee4c672120605d6247214d6257215d6267216d6277217d6287218d6297219d62ae5c672290463b2a5997221730f00d62bc6722a0404d62ce6722bd62d99997310721395722cd801d62de5722b731195ec8f722d731292722d7313722d95ed93722d7314e6c6722a050c4c0eb0e5c6722a050c4c0e83004c0e7315d9012e404c0e9a8c722e018c8c722e020273167317d62e721ad62f721bd630721cd631721dd632b2a5731801a7d633b27201731900ecedef722096830401937221731a93db63087222720192c17222997203722393c27222720ced722096830601721feded93c27224720c928c7228029591b17209731b9d9c720a7e722d05731c999d9c720a7e722d05731d7223938c7228017209eded93c27229e4c67212050e928c7231029d9c720a7e721305731e938c723101720993c27232721e937233b2db63087232731f00ed95722cd801d634e5722b732095ec8f723473219272347322d802d635b2a5732301a7d636b2db6308723573240186027202c17235eded928c7236029d9c720a7e7234057325938c723601720993c27235c2722a95ed9372347326e6c6722a050c4c0ed802d635e5c6722a050c4c0e83004c0ed636b1723593b4ad7235d901374c0e86028c7237019d9c7e8c72370205720a732773287236adb4a573299a732a7236d9013763d801d639b2db63087237732b0186027202c1723795938c72390172098602c272378c72390286027202732c732d732e93cbc3722a8c723301d808d620b2a5732f00d621db63087220d622b2722173300186027202c17220d6238c722202d6249172117331d625e4c672120711d626b2a5733200d627b2db6308722673330186027202c1722696830c01721f938c7222017209ec92722395720b72089a720ab27207733400ed7224927223721193b27201733500b2722173360093c27220c2a793e4c67220040e720c95ed72249272237211d801d628e4c672200559ed938c722801720f908c722802720d93e4c6722005598602720f9590997210720db272257337009a7210b27225733800721093c672200611720693e4c67220070e720993b172219593b172097339733a733b93c27226721eeced938c7227017209928c722702720a93720a733c733dd1938cb2db63087212733e0001733f",
      "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": "bac1b274029fa1ec0391c06ec355ef30d889e92aa5e64277f38b7e9243399cbf",
          "index": 0,
          "amount": 1,
          "name": "Odysseus",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "110380b8b5fa5180a8d6b90780d0918e8601",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[11000000000,1000000000,18000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "68a9f424a34e6e94a09154be868c8536e4af88f18b50ff3a22269b2e8c574296",
      "mainChain": true
    },
    {
      "boxId": "6c9ea5d53ab05e73e840fa22ba4ed0c99c73d536f2b69c7f62292d62c4a53668",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 2,
      "globalIndex": 39302548,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "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": "b7237145929afafe72119c09b34a45ee39f5ec64a5d1598308e52424e88eeb5d",
          "index": 0,
          "amount": 1,
          "name": "Hector",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "110380e08bb45980a8d6b90780f8e7c78d01",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[12000000000,1000000000,19000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "51a2a6a8dfebbee75ef10f8feaa63d5555c63343099b9f4f9e3335ebb90abd08",
      "mainChain": true
    },
    {
      "boxId": "b6762e6d104fe598912b7afb9d81e6ed8578485213f438bbf73c9019feebee8f",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 3,
      "globalIndex": 39302549,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "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": "28a36d4aca0cc7bd4568738febed36794b53c54525d0b59752506005b2169980",
          "index": 0,
          "amount": 1,
          "name": "Eros",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "110380b8b5fa5180a8d6b90780d0918e8601",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[11000000000,1000000000,18000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "e8457b990a7648438f0cb3a161e35d3d76dae5847beec20017a86fa135689930",
      "mainChain": true
    },
    {
      "boxId": "c1c37275bd671fdf06b383f2668eb9af4793f736a15ee81ce530666a39da4ce6",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 4,
      "globalIndex": 39302550,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "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": "GZJ5yvPXrP52Pc7JYv5gt8E5hQbQTgwVm6xiRkWLqh3gdEgsWtHomjmDVCPdFGoscG3YZ5z9yWENPJG3Fnn12KrJ89Zc2gsAa3uBYugxaut69LWsi2UTjjXs9xD7Sf26SvpUmoBBqj1i6duhL76iDSJVihZh7yZiZMLRuSBmiUxsf4S16CVtthYwvZ9Z9LyFGEPXTcWiuTHzG3HhPyji429vfRqyZXXTcEWckAim4k9vU3nZ7Q4dAzqjZDJpgD5QJKP8co7uUJEu4Ef1drk1ha2hPH6ZbC9h2awzbUbCqBVUgPkYZRY5cxHSJGQJw7jAQsd6As2eabaH5iwByu7FKvXbNMiWnqHUPekr6bAdja5gYBnHak4sopo5ihXs1TYufRwp6cxGD1Dt8VWLWJHQKgmSzVmd7CGJfZpVg354Q4YSdK93yxLMUEWdnsatu42UNWbwUGpqsgg3inKDdBYgG6mD2BpmJknMbahrMpaCQhcySZcweySkD7E9Ab5oPPbjV8J3XzoFM344C7iBmXPhYEjenocn21WXFkM1dzQQqRju26zVJFtBdgUxc9DUW9WUTxuE6yu8YLjWNRW5zxXy1zVqsmaVmRa7dSDRg63YrsfrBgFXHSqKongEnXzDnzcHV8qirE7NVEqXT6NpfLDAwB7oxyPx3xwz1b4zy2PbXjG7w5N4MaVYvSG13JRxM5pxEgHF1fwh2SuvGKcF3dZnVEPJDChGFDgc2CmZbn1k4UAcheS7ZvVXBRmiZUcYehE9igQPum22yTvAgtLzkAocvM7yzdPGbm32DVMkiJRKkYEMizQvS3RjtXpUrLSDacRpwc1qxF1DKFbGF8JcdC5peR69mhyQT9r6yiVgLYBWD6t3M5otQ4jDCWUkeLy6zfNwead8VPU1DeTtwZ5neeGR4MwMYZbvvEJSFsZFJDwxEnRxjSzwzkG7SCnLmDUAhjbBXT3fXmoEMB4S7b34qGYk8V9GVhcBEyTYYQStEZxdDsKQUvd14twknkna6xkjFJWU6t18vvdxYpK7PkyJBtrXKyj7R3gesqDmgRaDTnPB47MKaJ3K953uVVefrfFovRQ4fibP6GcH2m6thn2pDvPwTvufXSCAxMpheER65DaSKa3UZnXwKr4hTN7sCPPDYDL3zCoFJBSFK9qoy28jA67Kiet4kbnBjj3c3Z66fC6EXKcS5EDCwNXBSBofR1zoFXdN29yS4dUbjMPygS9v6dnySyP7GiCrxhpi9stkbT7BG317SCP3LEcVBC6kLZwLRtbgsbf61bpcunVvTjEKxvQc66se5k66qfk3fwGMAiP7YypepNFtgfcy6YXQwCUGC8CNreCLh6ae6Q2PapspTAxmMu7m8QMmPMnSiUwr2soea8ui5fn8yMFy4ZnFpnJtvny7Bm2KmYfjC4gwKtg89HJD3KuAQKN83oXiS8h9YSEiYsTzAoXgG8h7ecmb3Z5Y9vxy9T9NGx5CBxsBa8QiwBfdy5C3C6f4pX8eeuWoqAW5HFuVy96vKyQWTVEgJ6jtDgEcRHJkB1uCZdawAXttNbZnj5xF4Ev5X4xe5Lptgr2Vcr2n9WuoDChohbsJSFMP2ucrDAzq1DuDCC1dUH5Vk8pFV9CYeyrgndWwb4XTZAJ1APMtZhLTcRtGJ9piaMEZZEvyK3ZidRWVguAWdGR5Xg3o1SeM95UGwhfJHmNDfnXekcFfy9zBZ8pprWucVUXQsjeCbde1ftEukPmjCVVUc4kCTpe7sq8FVjpixso4ytHcR2fpwMM1nDc8SH1DDtVYC82dfi2n2QX1h3qatt",
      "assets": [
        {
          "tokenId": "8c0aa986eaa852f84e5cc55f4d50d7dcdba5cae4e2c37fc5227e36213e69f4b3",
          "index": 0,
          "amount": 1,
          "name": "Stesichorus",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "110380c0b2cd3b80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[8000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "df421b6ea8ae77e90bd2a44dcacfd6d38bcab9b330ee92216d0a0e2d5b71f200",
      "mainChain": true
    },
    {
      "boxId": "1dc4fbaae47713d8cf7f246bdcedce3200f12be49c95bafe86c3f0c9d51129c8",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 5,
      "globalIndex": 39302551,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "ergoTree": "1040040204000500040405000400040404000402040004000406050004000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f04000400040404140406040005d00f040405d00f040004060406040005000100010104000402050004020400040204000400040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed81fd601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60b8f720a7208d60ce4c6a7040ed60ddb6903db6503fed60ee4c6a70559d60f8c720e01d6108c720e02d611b272077303017304d612b2db6501fe730500d613e4c672120404d614b2a5730601a7d615db63087214d616c17214d617860272027216d618b272157307017217d619b2a5730801a7d61adb63087219d61bc17219d61c86027202721bd61db2721a730901721cd61ee4c6a7080ed61f93c5b2a4730a00c5a7ea02eb02ea02d1720bcdeeb4720c730bb1720cd19591720d720f9591720d7210d814d620ec92720a7208ed917211730c92720a7211d621b1a5d622b2a5730d00d6239c730ee4c672120605d6247214d6257215d6267216d6277217d6287218d6297219d62ae5c672290463b2a5997221730f00d62bc6722a0404d62ce6722bd62d99997310721395722cd801d62de5722b731195ec8f722d731292722d7313722d95ed93722d7314e6c6722a050c4c0eb0e5c6722a050c4c0e83004c0e7315d9012e404c0e9a8c722e018c8c722e020273167317d62e721ad62f721bd630721cd631721dd632b2a5731801a7d633b27201731900ecedef722096830401937221731a93db63087222720192c17222997203722393c27222720ced722096830601721feded93c27224720c928c7228029591b17209731b9d9c720a7e722d05731c999d9c720a7e722d05731d7223938c7228017209eded93c27229e4c67212050e928c7231029d9c720a7e721305731e938c723101720993c27232721e937233b2db63087232731f00ed95722cd801d634e5722b732095ec8f723473219272347322d802d635b2a5732301a7d636b2db6308723573240186027202c17235eded928c7236029d9c720a7e7234057325938c723601720993c27235c2722a95ed9372347326e6c6722a050c4c0ed802d635e5c6722a050c4c0e83004c0ed636b1723593b4ad7235d901374c0e86028c7237019d9c7e8c72370205720a732773287236adb4a573299a732a7236d9013763d801d639b2db63087237732b0186027202c1723795938c72390172098602c272378c72390286027202732c732d732e93cbc3722a8c723301d808d620b2a5732f00d621db63087220d622b2722173300186027202c17220d6238c722202d6249172117331d625e4c672120711d626b2a5733200d627b2db6308722673330186027202c1722696830c01721f938c7222017209ec92722395720b72089a720ab27207733400ed7224927223721193b27201733500b2722173360093c27220c2a793e4c67220040e720c95ed72249272237211d801d628e4c672200559ed938c722801720f908c722802720d93e4c6722005598602720f9590997210720db272257337009a7210b27225733800721093c672200611720693e4c67220070e720993b172219593b172097339733a733b93c27226721eeced938c7227017209928c722702720a93720a733c733dd1938cb2db63087212733e0001733f",
      "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": "7387feb04e7118768341947abf8b0addd3d9090c24641eb361d22afdae40e65d",
          "index": 0,
          "amount": 1,
          "name": "Alexander",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "11038088e2ed6080a8d6b90780a0be819501",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[13000000000,1000000000,20000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "de308c2abc1cf4fb500b41724c759d4f896c0d0e94dab530ca8cd849eda59b9c",
      "mainChain": true
    },
    {
      "boxId": "58c3ffe6257d6738994ad7ec86a820793cd41f3c7d34faec5d4fda41bfa6e64a",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 6,
      "globalIndex": 39302552,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "ergoTree": "1040040204000500040405000400040404000402040004000406050004000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f04000400040404140406040005d00f040405d00f040004060406040005000100010104000402050004020400040204000400040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed81fd601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60b8f720a7208d60ce4c6a7040ed60ddb6903db6503fed60ee4c6a70559d60f8c720e01d6108c720e02d611b272077303017304d612b2db6501fe730500d613e4c672120404d614b2a5730601a7d615db63087214d616c17214d617860272027216d618b272157307017217d619b2a5730801a7d61adb63087219d61bc17219d61c86027202721bd61db2721a730901721cd61ee4c6a7080ed61f93c5b2a4730a00c5a7ea02eb02ea02d1720bcdeeb4720c730bb1720cd19591720d720f9591720d7210d814d620ec92720a7208ed917211730c92720a7211d621b1a5d622b2a5730d00d6239c730ee4c672120605d6247214d6257215d6267216d6277217d6287218d6297219d62ae5c672290463b2a5997221730f00d62bc6722a0404d62ce6722bd62d99997310721395722cd801d62de5722b731195ec8f722d731292722d7313722d95ed93722d7314e6c6722a050c4c0eb0e5c6722a050c4c0e83004c0e7315d9012e404c0e9a8c722e018c8c722e020273167317d62e721ad62f721bd630721cd631721dd632b2a5731801a7d633b27201731900ecedef722096830401937221731a93db63087222720192c17222997203722393c27222720ced722096830601721feded93c27224720c928c7228029591b17209731b9d9c720a7e722d05731c999d9c720a7e722d05731d7223938c7228017209eded93c27229e4c67212050e928c7231029d9c720a7e721305731e938c723101720993c27232721e937233b2db63087232731f00ed95722cd801d634e5722b732095ec8f723473219272347322d802d635b2a5732301a7d636b2db6308723573240186027202c17235eded928c7236029d9c720a7e7234057325938c723601720993c27235c2722a95ed9372347326e6c6722a050c4c0ed802d635e5c6722a050c4c0e83004c0ed636b1723593b4ad7235d901374c0e86028c7237019d9c7e8c72370205720a732773287236adb4a573299a732a7236d9013763d801d639b2db63087237732b0186027202c1723795938c72390172098602c272378c72390286027202732c732d732e93cbc3722a8c723301d808d620b2a5732f00d621db63087220d622b2722173300186027202c17220d6238c722202d6249172117331d625e4c672120711d626b2a5733200d627b2db6308722673330186027202c1722696830c01721f938c7222017209ec92722395720b72089a720ab27207733400ed7224927223721193b27201733500b2722173360093c27220c2a793e4c67220040e720c95ed72249272237211d801d628e4c672200559ed938c722801720f908c722802720d93e4c6722005598602720f9590997210720db272257337009a7210b27225733800721093c672200611720693e4c67220070e720993b172219593b172097339733a733b93c27226721eeced938c7227017209928c722702720a93720a733c733dd1938cb2db63087212733e0001733f",
      "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": "e011e2277a8cadcde5479fbef6a06b52a71120151dfe4c81b131b73d9c3f5ebc",
          "index": 0,
          "amount": 1,
          "name": "Aristides",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "110380e888874380a8d6b9078080e59a77",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[9000000000,1000000000,16000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "fe3ec7af5e1d43d5ef4cab3a76da4aceaf5580f97bb000a743f13300febe962b",
      "mainChain": true
    },
    {
      "boxId": "f6b602c75795e596747b2c0d6dadc2d4e0d8b9f7562b22f08337de74c6755b73",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 7,
      "globalIndex": 39302553,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "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": "4438fc94afc3da211cbbd0988cb4fe539fd5562e87b2d88eea90338dd99fda42",
          "index": 0,
          "amount": 1,
          "name": "Apollo",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "110380b8b5fa5180a8d6b90780d0918e8601",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[11000000000,1000000000,18000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "ad74b62344134cbab6fad57a6e1d89e6179f66f3e30721bcdd87df75aab3cfc6",
      "mainChain": true
    },
    {
      "boxId": "c2d2a459d534e78636fde596847054fe812dfa37a1f91b44d1135d7da9861cb7",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
      "blockId": "54d2993e9a2ee555eb73e02d13a3cc6d7355128a3d960b0cb761ab71edb563ea",
      "value": 15000000,
      "index": 8,
      "globalIndex": 39302554,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "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": "b5a37518959c5d00455562f718502dfbfabd707b3499fee42e360712304d8a59",
          "index": 0,
          "amount": 1,
          "name": "Aeschylus",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980ceb28ade6380de96cbe263",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1713434416000,1714039216000]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780a8bbd47e",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,17000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
        }
      },
      "spentTransactionId": "42c2a553f39e3a9b5cdb9c5fb4fa516aa09c9c12ea68130ebd925cb7dd7b82b6",
      "mainChain": true
    },
    {
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      "index": 9,
      "globalIndex": 39302555,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "ergoTree": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(5b1574,267d10,...)))}",
      "address": "9fDB8QW4AgFJvRjfesjAKU5bLRjAohe5BGXgnwfHAAeccKyEECh",
      "assets": [
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          "type": "EIP-004"
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      "additionalRegisters": {},
      "spentTransactionId": "ee3b6c52ce900764797507d893843ac5971cb214487b6c73898db26f9f0e946a",
      "mainChain": true
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    {
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      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "ergoTree": "0008cd03240e71da7ba42ff1e2f68c425ee64ca7d9504a1c84b0c95de4a6effe68804d1d",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(240e71,dfb102,...)))}",
      "address": "9gjghouPwq9TCKyFAAvHPsoE1n9moZWec9oKeRzAjnV9p4hAzvo",
      "assets": [
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          "name": "AHT",
          "decimals": 4,
          "type": "EIP-004"
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      ],
      "additionalRegisters": {},
      "spentTransactionId": "343fcbef71668b38000ace6621b410b707ae21bee9c2f927c1a6e192d4b808bc",
      "mainChain": true
    },
    {
      "boxId": "29b24603bb8dad1219afe5d2a9026e1c3b9fb25eb6d41bdcd586acd203d6deff",
      "transactionId": "c67635f794efe35484235c5ddfa3afeddfc8c95f5edcd00b3d2a54384913857f",
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      "index": 11,
      "globalIndex": 39302557,
      "creationHeight": 1245543,
      "settlementHeight": 1245546,
      "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)}",
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      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "97fd32cdd1278dc8c95a1fb5c401b87fbbce99aac082fe6b734ca7ca02b6ae9c",
      "mainChain": true
    }
  ],
  "size": 14553,
  "isUnconfirmed": false
}