Ad
Inputs (199)
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
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Value:
7.93 ERG
Tokens:
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Output transaction:
Settlement height:
Value:
0.0001 ERG
Tokens:
38.17
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.00003996 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.00003996 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
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0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
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0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
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0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
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0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
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Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Outputs (15)
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
2.41 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
2.41 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
2.41 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
1.5 ERG
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Transaction Details
Status: Confirmed
Size: 38.92 KB
Received time: 9/3/2023 06:52:17 AM
Included in blocks: 1,082,926
Confirmations: 673,343
Total coins transferred: 8.9 ERG
Fees: 0.005 ERG
Fees per byte: 0.000000125 ERG
Raw Transaction Data
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  "index": 20,
  "globalIndex": 5770477,
  "numConfirmations": 673343,
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      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
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          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "ce5752291ac263a773dc273a608bc5cc3e4730551bf1a10a9760d1daea6f3158",
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      "spendingProof": "868d3555e65ded53e6d0fe11029d0b00b56123ff5cbe2316c3e039d001bd7ccdebb3afe21894c8977355c36c34ce1bcaed0c69ce6658d909",
      "outputBlockId": "fce4b99d60a8ef0079512d69e8cd20508539441f99d06553fedc15a988796113",
      "outputTransactionId": "77fa82128f75bf0968b367f2779b8cb797c201e38bbc979db2ab24f4bd21ff75",
      "outputIndex": 0,
      "outputGlobalIndex": 32210116,
      "outputCreatedAt": 1080464,
      "outputSettledAt": 1080466,
      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
        {
          "tokenId": "c9d5e239fba9dc165a0f92b648a01c29391c2529515c0584480d5d88d94bca31",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #205",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "0b9ec5df7f99fa9822ba9768a2c404b47f1298cd36630fe0c6b38014c06ffae4",
      "value": 5000000,
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      "outputBlockId": "fce4b99d60a8ef0079512d69e8cd20508539441f99d06553fedc15a988796113",
      "outputTransactionId": "78ea5752d37b5f613bc8eb225e7d9ae6f3c37e07239a4e5c15417909e340b227",
      "outputIndex": 0,
      "outputGlobalIndex": 32210119,
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      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
        {
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          "index": 0,
          "amount": 1,
          "name": "ClayBob #730",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "939cca682a8fbd353f86546a11973a427cb26f19ded6d34e7d21dc99136e4192",
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      "spendingProof": "f732ec7f2517b453eef90aeaeecd60dfcd727d1d5e70dbfc4525e3c8790e3187de6686fc11a787174730abb047e68c813e00dc59796a2207",
      "outputBlockId": "fce4b99d60a8ef0079512d69e8cd20508539441f99d06553fedc15a988796113",
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      "outputIndex": 0,
      "outputGlobalIndex": 32210122,
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      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
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          "name": "ClayBob #591",
          "decimals": 0,
          "type": "EIP-004"
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      ],
      "additionalRegisters": {}
    },
    {
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      "outputBlockId": "fce4b99d60a8ef0079512d69e8cd20508539441f99d06553fedc15a988796113",
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      "outputIndex": 0,
      "outputGlobalIndex": 32210167,
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      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
        {
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          "index": 0,
          "amount": 1,
          "name": "ClayBob #549",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
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      "spendingProof": "b4ae049742a48132b51ab3d09d5b3f40c09cc054f3a8aaf8f891e8c51073f69187d0876afe9280e297122f0bed629cb94c9b18a1f8114d41",
      "outputBlockId": "fce4b99d60a8ef0079512d69e8cd20508539441f99d06553fedc15a988796113",
      "outputTransactionId": "b6d18ccf719d5d395e69f6005b0feeae384f93d198d6c1025747185423bb30f0",
      "outputIndex": 0,
      "outputGlobalIndex": 32210176,
      "outputCreatedAt": 1080464,
      "outputSettledAt": 1080466,
      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
        {
          "tokenId": "c0c89d2dc5585e0e1be1aee28e6edbbbd7d662e62f68e9c8765abe375ae81d2f",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #360",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "361427481c33515d27df083eddfb430e0a0116a9d0764ebc422b4d5faf420151",
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      "spendingProof": "76b275f7e3ded8c8aa9a64a417c2ed63e945aaf9dad9f3845ead2054a9c60ffe2f337bc6acd14cd63196b6857a597a0616f7aff2a3d49ef8",
      "outputBlockId": "5f018f75a488a85b94d68a27bf694f82bc386ef256a798df6288d1b41a5e2cca",
      "outputTransactionId": "786148114ac2b01ff84513f838474a46ae44b2a0c0c2ce5e7d5afe0799d5b269",
      "outputIndex": 0,
      "outputGlobalIndex": 32210756,
      "outputCreatedAt": 1080482,
      "outputSettledAt": 1080484,
      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
        {
          "tokenId": "d83b6ece698452f223b774083ee5358b3848fd672510094f39f1af5a6b9a03af",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #853",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "889219d430ee542d2272f44a0f17617a27a6927583165fbdd41fa10807521e0f",
      "value": 5000000,
      "index": 197,
      "spendingProof": "453b8d9e3e4c04a4982e98e138ce3c88c773da9c4dca095a15dab84c6f4b4f22bb37a1c8c17f5a784453d90900d6ce8d793567b0ca3d1bbe",
      "outputBlockId": "5f018f75a488a85b94d68a27bf694f82bc386ef256a798df6288d1b41a5e2cca",
      "outputTransactionId": "91aed7e57f77db51d70e1ac67594db7a693eee238a9984aae815122c43742580",
      "outputIndex": 0,
      "outputGlobalIndex": 32210759,
      "outputCreatedAt": 1080482,
      "outputSettledAt": 1080484,
      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
        {
          "tokenId": "636ef9dfaa97be6373eddf52744a3cd4dcafa9d1d3bc09cf2123f6191a4e2c17",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #799",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    },
    {
      "boxId": "136b1acb49154df37958252e8eb4aaa2b9c6311f6c8c240b1adca94defb2746e",
      "value": 5000000,
      "index": 198,
      "spendingProof": "104289c9f2430db41b98d45306e948004609c56776c26e92ff4f4be5c1a530c273b6f48465d1da7c07d087a889e750102a8c419cea563322",
      "outputBlockId": "5f018f75a488a85b94d68a27bf694f82bc386ef256a798df6288d1b41a5e2cca",
      "outputTransactionId": "1787a3d7a50a7f77f26545a5e29ec7ce3b84d768aeb26954a3d120fc9bf6a47c",
      "outputIndex": 0,
      "outputGlobalIndex": 32210762,
      "outputCreatedAt": 1080482,
      "outputSettledAt": 1080484,
      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
        {
          "tokenId": "db651d1dbf6ee99e8db0bf24c431b33fb4a065e2485307c3df85c8b849e75867",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #850",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [
    {
      "boxId": "573d9010b852894b9f99bc072933e6cfa115b490f857451e385dbc2e8448cf7c",
      "value": 4219364,
      "index": 0,
      "outputBlockId": "b3cfb684232fe21e89a8132c966b08c6772b72369822c397d25a7bc8e98c9bda",
      "outputTransactionId": "aa58e9d389d3044fda4201159d5d62752e0820f8d0b8506cec28ac4fd0ea826e",
      "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": "0428",
          "sigmaType": "SInt",
          "renderedValue": "20"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "d3ba3925d9f15e1444fcd27e33b6823da6b65653945387cd39cbc8bffe0af3a4",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 0,
      "globalIndex": 32314268,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "17a494bdc94813bfa1561a9acb301d666f4c79bf5b7f983625fac5a43512f216",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #9",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62d0abb4b1d162",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694550625000]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "bddd1a3f4f50c59a1f0b03974ba15b437102b104665d9b013de503191ba05363",
      "mainChain": true
    },
    {
      "boxId": "8c0e650ab5a67e8521d9cdf6b18075b922449f75306f3a5ab72caeab29767a5a",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 1,
      "globalIndex": 32314269,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "0baf57e2221df898dc6b4b9d23a8b8d2a6dd6f47b045fc181e984198eef444c8",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #505",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "133846db8c4bfd85e934057946e6da79ecaf7d19578a9baf7171d6bf57da2de9",
      "mainChain": true
    },
    {
      "boxId": "4eed253022526ca3e34fdc1d2f03b0c51cca8b08d3b1170ee72bd74d83ee868d",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 2,
      "globalIndex": 32314270,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "1039dc8a5dd773f154f42663e562c76e363436ffb482bd02bc08ce86e672edf4",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #102",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "baee2e2625a63742702e4a8ee756da608d678d750fb712f50df13bf08f652e1b",
      "mainChain": true
    },
    {
      "boxId": "8974d52aae3a5a10b83d40a0b9f16112568fd45c048369f69d93c5021e7c162c",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 3,
      "globalIndex": 32314271,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "091945e29ec7afdf1ec95bfd709c4229966e63d783e0b532b51a93f25285f05c",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #154",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "fe472d29154b3861f4844f7059fe5ab8cf870ecd7bf2130ec3fa1b0732d7e8fb",
      "mainChain": true
    },
    {
      "boxId": "7dd20f779a8bcc5259ebb4a2552fc9763e756a691d423667bb808d7157d2fa50",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 4,
      "globalIndex": 32314272,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "17cc80631f5a1a4b48ba7f80f2be0833d397b8891edfa5fd5b099a749364cc3d",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #367",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "bdd9177813e106fbcca785df6974fe2aa0f1c578f8b74a81b1d30e386e559db9",
      "mainChain": true
    },
    {
      "boxId": "15e7800bdc492f6f0ea8bb8682f2c0eb9389f78a624c08f7609c631129f31af4",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 5,
      "globalIndex": 32314273,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "3NtW3QbiLwaF7f2h7NyiFZwSV3LqNwFNBH5HQgzeGtttvsLCS4e19bjkpDbuNbzBXtjvK3eyi94G9YNjeR94F4ix5iAXHSwmSsZ2ftbMCBfxf9JfgouBAvbrcKoDnioJmQdTfQLi8ubzsnzfi3aCE9sV1mXLxob6Dto5XCCGhuBXEB631qRpxaWkASSpgwHhAJdJQcM1ikTtfTXcVmx7n3rtQ83i1xvb4zaJYHA4SGBwT4je2dFd27k8gRpvTgk5RbxxzsiBTpdbyB1a2eEfHfyQztYrC7NPD6M94aiHKtfzCvXjGZPpFohMLsdV4H8yggtqeiay3Nxj2MctjkyTWfKkr1dbWit9bHGyT58fXMpPbBr96NQfZsPNgWFMpusN2VJo9LyMFaGZYZgDyzykTuD6UvwfC2GBLuW1bk12YvuTbqhszbxVaWjf47Kzm13xkotdseL6a7NTULKFbFv8uLUVindCiqu4Gbv26V6kh9xCSM9vPvbqw67uH4QXUcj2N2THFS8CjZkatjHBQhMzDngiAyd8jKfhqa9w6N87S2jJNnZoKT87tKqLXA5oyvVfz4BNFqhHANfGfrQvAXLfoiZ2nCRyYYcy1BCvQ8TWiwf48MPuhKcipa5UdrndgAe7EZrVB3SbFnP7a3KfHkX36LfZBxbH7V2g9C3a9JnkkFhAFM1wfBYrvbJbSN8siGqEusfPh3D6UFAwNNN9aAKiYXZE3H1u4zVb8trNawRp7Ye3Rr8bTBEqX65xs1jpdZCzHUzQMikjBsUaRrCtkWut3PEtmVeQXUVRKwz2eYFaE4sX2zUuMuswKY911Lw38jNHcmUdwXYXCEEZNGY4b2LbMjyMpFHcnM5PMdoAPtx21LTB2oSMqGGcDPr5kigNeYUacjxEjimhMSnxYiVhnoQPKjftvzJwtvdT55fewwLGcRUDP8Koa31pkjubLtpPbiXCyiZ4iXZ2c1M82Wpxsb6EpGvkuhm5iiUi6Kdj6Ya4fzJhmgZLJZu57TxxTr1AB3EfH4AYqnKhrJeBwb5jcv5YD8vtWVeZ53wDaBGyEgkCZxZvgff4rkX2yBu3pCpQZheTxUepQzykqNJck3Y2gMJcC8nxYyjbtpgckReo2LT4bZi5DKsyv6QNWruenSEd3KavrMuyaiBu3LFxxvKwGJFXfZiEku5pALnbi15npqHuxhmwXwhbQFXUVfwviHsJH71qY889oQjERkweQkEB9AFk8hkkLG5aGyWruGLJa3546CPc6Zvbqwt33CZGbpo7jcuuG4rP4G2dpefASG8H45A8NeiGcQq3LXCvAw9MyzLmkVpvFG71nqurqdJCexWcawiLC1QiQwis4AFn9qgf4TLNprpAHPWr1nYAXa78f8DiXy5ahCNjArVq1SdseuFG3S1aoCEP8hbTWmHzBeRmJVsGhJXpNi2h9UiePxWsBBzVm5usMpsaBuckmxxXJyQAantCqFCVXcB71ZLi3pUjTYv2E4Ldf8QEjuSHMqmUv8HWvUudHRiPpCnqoyxyzjQtjbbcqAaSo7zKF1i3d6swUQbcjyULQTkL2oPwYy6vB7yenYXrCEWmyV85iH3wdYzdJj6CYoD5vRKAoNh1kMxZ82nkyB7KoCqr3AePVdSoWned8LMURXdGDdGCpVr7QtcHBL2E3RY4A3drPYpc1DWct8gwPGbowLJkHLNhPwsxTuLReLuotmT7Gheyd6NYUFtz1aWM516uNdDDg5bEPGXzJAGEx1UjZArrStByZcMKRDYVMG6NtNjLvDJCZEvLgBRG1Bi79mgBBbV75",
      "assets": [
        {
          "tokenId": "25d9b7679a60a4e0130029ac1962bc32f1a371656649a348d8e2a14b91b8ff17",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #899",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "ff1762d5d34df58d6c492ef9f25cf529dfbe1e370b68d19ad81f4eb1152fcd44",
      "mainChain": true
    },
    {
      "boxId": "10ff94fb320a3478ab9c482e028e1acac003c352a26759ea4cab8eb65267ca5c",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 6,
      "globalIndex": 32314274,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "17ede47e738e4a24b95852aa4583ceb6ab2bc8c9dc9317f606445089232a710b",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #858",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "059e04e8eccc6f9ae32fd9aec4b7978458e17bdd9354731d1120ea12a67816d5",
      "mainChain": true
    },
    {
      "boxId": "21db2e6646203fd1bf5b5a9a566cce9a694483d4fb64aac18e6945cb8a1231a4",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 7,
      "globalIndex": 32314275,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "ergoTree": "103f040204000500040405000400040404000402040004000406050004000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f0400040404140406040005d00f040405d00f040004060406040005000100010104000402050004020400040204000400040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed81fd601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60b8f720a7208d60ce4c6a7040ed60ddb6903db6503fed60ee4c6a70559d60f8c720e01d6108c720e02d611b272077303017304d612b2db6501fe730500d613e4c672120404d614b2a5730601a7d615db63087214d616c17214d617860272027216d618b272157307017217d619b2a5730801a7d61adb63087219d61bc17219d61c86027202721bd61db2721a730901721cd61ee4c6a7080ed61f93c5b2a4730a00c5a7ea02eb02ea02d1720bcdeeb4720c730bb1720cd19591720d720f9591720d7210d814d620ec92720a7208ed917211730c92720a7211d621b1a5d622b2a5730d00d6239c730ee4c672120605d6247214d6257215d6267216d6277217d6287218d6297219d62ae5c672290463b2a5997221730f00d62bc6722a0404d62ce6722bd62d99997310721395722cd801d62de5722b731195ec8f722d731292722d7313722d95ed93722d7314e6c6722a050c4c0eb0e5c6722a050c4c0e83004c0e7315d9012e404c0e9a8c722e018c8c722e020273167317d62e721ad62f721bd630721cd631721dd632b2a5731801a7d633b27201731900ecedef722096830401937221731a93db63087222720192c17222997203722393c27222720ced722096830601721feded93c27224720c928c7228029591b17209731b9d9c720a7e722d05731c999d9c720a7e722d05731d7223938c7228017209eded93c27229e4c67212050e928c7231029d9c720a7e721305731e938c723101720993c27232721e937233b2db63087232731f00ed95722cd801d634e4722b95ec8f723473209272347321d802d635b2a5732201a7d636b2db6308723573230186027202c17235eded928c7236029d9c720a7e7234057324938c723601720993c27235c2722a95ed9372347325e6c6722a050c4c0ed802d635e5c6722a050c4c0e83004c0ed636b1723593b4ad7235d901374c0e86028c7237019d9c7e8c72370205720a732673277236adb4a573289a73297236d9013763d801d639b2db63087237732a0186027202c1723795938c72390172098602c272378c72390286027202732b732c732d93cbc3722a8c723301d808d620b2a5732e00d621db63087220d622b27221732f0186027202c17220d6238c722202d6249172117330d625e4c672120711d626b2a5733100d627b2db6308722673320186027202c1722696830c01721f938c7222017209ec92722395720b72089a720ab27207733300ed7224927223721193b27201733400b2722173350093c27220c2a793e4c67220040e720c95ed72249272237211d801d628e4c672200559ed938c722801720f908c722802720d93e4c6722005598602720f9590997210720db272257336009a7210b27225733700721093c672200611720693e4c67220070e720993b172219593b1720973387339733a93c27226721eeced938c7227017209928c722702720a93720a733b733cd1938cb2db63087212733d0001733e",
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "3e16999ff2aa1db92a4f470bdd82a65f3f6dc2ae5bae1dd4adc31362c5ffb862",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #399",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "7b9176a619881d962ab6d2c1cd9bf64d80ffa09bd6293952d60d8ce36473b1d8",
      "mainChain": true
    },
    {
      "boxId": "d29db41da189a669ee067705302f013f85e3ddaf6e2c87f649d6acc7710c7464",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 8,
      "globalIndex": 32314276,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "4dccf7486b96f2b9b22219c878b867a5c1575f61bc311a7820cd08bda75c68eb",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #4",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "67202ff7bd2f85768b4b4e06221cdfe35c5adc4e8a37f9518bb2961139527891",
      "mainChain": true
    },
    {
      "boxId": "20ec191a93da668a3ea90e68630e8eedf229b133023d73615a30aea27a0fc99c",
      "transactionId": "fe16eb46ebd25be8dd417499794890afdea184c8d6caaf4b87bb1b9352f04048",
      "blockId": "b3e3526bc5c7d1fd09cb8c951fada254c34f2b8dda17f9851048b2d91c1d0825",
      "value": 15000000,
      "index": 9,
      "globalIndex": 32314277,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "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: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: 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.get\n                if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](37)) && 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](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n                      })\n                  )} else { placeholder[Boolean](44) } }\n              )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](46))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](48)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](49))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), 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](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n      )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "4b200cc1d0463ac49d8423062944519dc0a3d3831be9c294ee469b502cebc783",
          "index": 0,
          "amount": 1,
          "name": "ClayBob #52",
          "decimals": 0,
          "type": "EIP-004"
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      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59c89ed49fcb62c88fefdfcf62",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1693726705572,1694330905572]"
        },
        "R6": {
          "serializedValue": "11038090dfc04a80a8d6b90780d88ee16f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000,15000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861"
        }
      },
      "spentTransactionId": "4e8025696f51296931bd0482e1bad3d5591ebf3760ce661d066ceb0d2ee6fe23",
      "mainChain": true
    },
    {
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      "index": 10,
      "globalIndex": 32314278,
      "creationHeight": 1082921,
      "settlementHeight": 1082926,
      "ergoTree": "0008cd03b224de202ad595a3001cfbf3eb4869181232dadd8a800dcb458cca5a7c4e4861",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b224de,edc874,...)))}",
      "address": "9hpG99DNwn3WzTChnYsHu629Er9AaAE2A9VYDsY9Jvu433SLeRU",
      "assets": [
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