Ad
Inputs (7)
Output transaction:
Settlement height:
Value:
0.005 ERG
Output transaction:
Settlement height:
Value:
0.005 ERG
Output transaction:
Settlement height:
Value:
21.15 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
89.8 ERG
Output transaction:
Settlement height:
Value:
0.003 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
135.99 ERG
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
800
Outputs (4)
Spent in transaction:
Settlement height:
Value:
220.01 ERG
Spent in transaction:
Settlement height:
Value:
26.64 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.3 ERG
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Transaction Details
Status: Confirmed
Size: 2.38 KB
Received time: 3/10/2024 09:12:00 PM
Included in blocks: 1,218,055
Confirmations: 558,534
Total coins transferred: 246.96 ERG
Fees: 0.005 ERG
Fees per byte: 0.000002055 ERG
Raw Transaction Data
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  "inclusionHeight": 1218055,
  "timestamp": 1710105120452,
  "index": 3,
  "globalIndex": 6794992,
  "numConfirmations": 558534,
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      "ergoTree": "10170400040004040402040204000400040604000406050404040400040004000500040204d00f05d00f05d00f010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed810d601e4c6a7040ed602db6903db6503fed603e4c6a70559d6048c720301d605b2db6501fe730000d606e4c672050404d607e4c6a70611d60899b272077301009c9d9972027204b27207730200b27207730300d609e4c6a7070ed60ab2a5730401a7d60bdb6308720ad60c830002d60dc1720ad60e8602720c720dd60fb2720b730501720ed610b2e4c6a7080c4d0e730600ea02eb02cdeeb472017307b17201d1959172027204959172028c720302d801d611b2a57308009683040193b1a5730993db63087211db6308a792c1721199c1a79c730ae4c67205060593c272117201d80ad611b2a5730b01a7d612720cd613b2db63087211730c0186027212c17211d614720ad615720bd616720dd617720ed618720fd619b2a5730d01a7d61ab2db63087219730e0186027212730f9683040193b1b5a4d9011b6393c2721bc2a77310ed928c7213029d9c72087e9973117206057312938c7213017209eded93c27214e4c67205050e928c7218029d9c72087e7206057313938c7218017209eded938c7210018c721a01928c721a028c72100293c2721972017314d1938cb2db63087205731500017316",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 1\n5: 0\n6: 0\n7: 3\n8: 0\n9: 3\n10: 2\n11: 2\n12: 0\n13: 0\n14: 0\n15: 0\n16: 1\n17: 1000\n18: 1000\n19: 1000\n20: false\n21: 0\n22: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Byte]].get\n  val l2 = CONTEXT.preHeader.timestamp\n  val tuple3 = SELF.R5[(Long, Long)].get\n  val l4 = tuple3._1\n  val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n  val i6 = box5.R4[Int].get\n  val coll7 = SELF.R6[Coll[Long]].get\n  val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n  val coll9 = SELF.R7[Coll[Byte]].get\n  val box10 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll11 = box10.tokens\n  val coll12 = Coll[Byte]()\n  val l13 = box10.value\n  val tuple14 = (coll12, l13)\n  val tuple15 = coll11.getOrElse(placeholder[Int](5), tuple14)\n  val tuple16 = SELF.R8[Coll[(Coll[Byte], Long)]].get(placeholder[Int](6))\n  proveDlog(decodePoint(coll1.slice(placeholder[Int](7), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n        val box17 = OUTPUTS(placeholder[Int](8))\n        allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](9), box17.tokens == SELF.tokens, box17.value >= SELF.value - placeholder[Long](10) * box5.R6[Long].get, box17.propositionBytes == coll1))\n      )} else {(\n        val box17 = OUTPUTS.getOrElse(placeholder[Int](11), SELF)\n        val coll18 = coll12\n        val tuple19 = box17.tokens.getOrElse(placeholder[Int](12), (coll18, box17.value))\n        val box20 = box10\n        val coll21 = coll11\n        val l22 = l13\n        val tuple23 = tuple14\n        val tuple24 = tuple15\n        val box25 = OUTPUTS.getOrElse(placeholder[Int](13), SELF)\n        val tuple26 = box25.tokens.getOrElse(placeholder[Int](14), (coll18, placeholder[Long](15)))\n        allOf(Coll[Boolean](INPUTS.filter({(box27: Box) => box27.propositionBytes == SELF.propositionBytes }).size == placeholder[Int](16), (tuple19._2 >= l8 * placeholder[Int](17) - i6.toLong / placeholder[Long](18)) && (tuple19._1 == coll9), ((box20.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple24._2 >= l8 * i6.toLong / placeholder[Long](19))) && (tuple24._1 == coll9), ((tuple16._1 == tuple26._1) && (tuple26._2 >= tuple16._2)) && (box25.propositionBytes == coll1)))\n      )} } else { placeholder[Boolean](20) }) && sigmaProp(box5.tokens(placeholder[Int](21))._1 == placeholder[Coll[Byte]](22))\n}",
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      "assets": [],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59ec908ba3c563eca0efe3c963",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1710104863798,1710709663798]"
        },
        "R6": {
          "serializedValue": "110380e0ac90e70c0002",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[220000000000,0,1]"
        },
        "R8": {
          "serializedValue": "0c4d0e022027cd91146138f19f82bc7bd605decd6e46ef45968cbcc128d76ab8d8809072fc020000",
          "sigmaType": "Coll[(Coll[SByte], SLong)]",
          "renderedValue": "[[27cd91146138f19f82bc7bd605decd6e46ef45968cbcc128d76ab8d8809072fc,1],[,0]]"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd02bc69a7d96dfd0523d74e3e2cc62ec6481bd4867cb5b3e2a72837131542cd45b0",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd02bc69a7d96dfd0523d74e3e2cc62ec6481bd4867cb5b3e2a72837131542cd45b0"
        }
      },
      "spentTransactionId": "2c14c4c8c28cdb4e6a0cd658f19cc3134691fa7c3591002f64ab4cf47f44646e",
      "mainChain": true
    },
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      "creationHeight": 1218053,
      "settlementHeight": 1218055,
      "ergoTree": "0008cd02bc69a7d96dfd0523d74e3e2cc62ec6481bd4867cb5b3e2a72837131542cd45b0",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bc69a7,79f7c4,...)))}",
      "address": "9fx3GKmJYtexVMSBdc7VBpVnQc24xdDjLFszxWjtEhiSM9UskCz",
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      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(240e71,dfb102,...)))}",
      "address": "9gjghouPwq9TCKyFAAvHPsoE1n9moZWec9oKeRzAjnV9p4hAzvo",
      "assets": [],
      "additionalRegisters": {},
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      "ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
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      "ergoTreeScript": "{sigmaProp(\n  allOf(\n    Coll[Boolean](\n      HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n        placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n      ), OUTPUTS.size == placeholder[Int](4)\n    )\n  )\n)}",
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      "mainChain": true
    }
  ],
  "size": 2433,
  "isUnconfirmed": false
}