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Transaction

8/15/2025 03:56:34 PM
ID: 7192f499e3...2ccb
Inputs (2)
#0
b1ae0df3d0c2...4917
Spent
Address:
PmKooeDy1PYr...jh8j
Output transaction:
773ec7fe11fe...bf27
Settlement height:
1,591,172
Value:
0.001 ERG
Tokens:
Loading assets...
#1
3d2cb69afbeb...20b8
Spent
Address:
9hPMZDMrGa7g...omgp
Output transaction:
773ec7fe11fe...bf27
Settlement height:
1,591,172
Value:
1.92 ERG
Tokens:
Loading assets...
Outputs (3)
#0
6f0a5b20190c...d37b
Unspent
Address:
AKqEGLPL17P2...Kif8
Settlement height:
1,591,173
Value:
0.001 ERG
Tokens:
Loading assets...
#1
c088bd561f1c...6fc4
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
9ccce82ca2bc...fa59
Settlement height:
1,591,173
Value:
0.0011 ERG
#2
84871bc0c2f5...4de5
Spent
Address:
9hPMZDMrGa7g...omgp
Spent in transaction:
88f9c7ed4cfc...e802
Settlement height:
1,591,173
Value:
1.92 ERG
Tokens:
Loading assets...
Transaction Details
Status: Confirmed
Size: 2.89 KB
Received time: 8/15/2025 03:56:34 PM
Included in blocks: 1,591,173
Confirmations: 178,499
Total coins transferred: 1.92 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000372 ERG
Raw Transaction Data
{
  "id": "7192f499e30291fc1d029c8f883432d4a2e706950d1f9bb5f12d3ed319542ccb",
  "blockId": "cb5a25b3c5fbe50376139cef9114ec428087a3c9eecff75bc915a1b23e30f1ad",
  "inclusionHeight": 1591173,
  "timestamp": 1755273394875,
  "index": 6,
  "globalIndex": 9355775,
  "numConfirmations": 178499,
  "inputs": [
    {
      "boxId": "b1ae0df3d0c2489c305565ce0fbbd26a805b61b0ace0ef310d6b058d6c794917",
      "value": 1000000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "86a9d0216829ada4a631df7458008f22cef53937418a6fb440852035fe5a18a7",
      "outputTransactionId": "773ec7fe11fef5df3907419fbe03673e7fa2a1ef4648f608b3dd1a950f3abf27",
      "outputIndex": 0,
      "outputGlobalIndex": 49476634,
      "outputCreatedAt": 1591171,
      "outputSettledAt": 1591172,
      "ergoTree": "1966040400040004000e2064e12e37811a1872977f91a5a04a7bf142a9752ac6f52a266a8bba4b7d5ddcb7d803d601b2db6308a7730000d602b2a5730100d603b2db63087202730200d196830201ed938c7201018c720301938c7201028c72030293cbc272027303",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: Coll(100,-31,46,55,-127,26,24,114,-105,127,-111,-91,-96,74,123,-15,66,-87,117,42,-58,-11,42,38,106,-117,-70,75,125,93,-36,-73)",
      "ergoTreeScript": "{\n  val tuple1 = SELF.tokens(placeholder[Int](0))\n  val box2 = OUTPUTS(placeholder[Int](1))\n  val tuple3 = box2.tokens(placeholder[Int](2))\n  sigmaProp(allOf(Coll[Boolean]((tuple1._1 == tuple3._1) && (tuple1._2 == tuple3._2), blake2b256(box2.propositionBytes) == placeholder[Coll[Byte]](3))))\n}",
      "address": "PmKooeDy1PYrXQZAuwDhALLyMEj9Vj2VMAQoZxbfrYGJeJcy4VazXnUVbVMzFJe6jVj73bwjPqQuarCrqiM826TCh5cX6UZub617qexTs5dHTCwmSjU6xoRQnF4VKMdf1fh8vqiSquZMbFCbjh8j",
      "assets": [
        {
          "tokenId": "c71aea526be5c3fa0a1925742574d30c27c7c2e36e4016903bdbb7bcc67dfe90",
          "index": 0,
          "amount": 8500000000001,
          "name": null,
          "decimals": null,
          "type": null
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "0500",
          "sigmaType": "SLong",
          "renderedValue": "0"
        },
        "R6": {
          "serializedValue": "1103000000",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[0,0,0]"
        },
        "R8": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R7": {
          "serializedValue": "0500",
          "sigmaType": "SLong",
          "renderedValue": "0"
        },
        "R9": {
          "serializedValue": "0ef6017b227469746c65223a225465737420626f756e7479222c226a7564676573223a5b223968504d5a444d72476137675a6e5a3348744e77614c62796d6236646463476e3257744e376e6859485667343733796f6d6770225d2c226465736372697074696f6e223a2254656d706f72616c2d66756e64696e6720546f6b656e20666f7220746865205465737420626f756e74792070726f6a6563742e20506c656173652c2065786368616e6765207468652041505420666f72207468652070726f6a65637420746f6b656e206f6e20426f756e746966756c206f6e63652074686520646561646c696e6520686173207061737365642e227d",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "7b227469746c65223a225465737420626f756e7479222c226a7564676573223a5b223968504d5a444d72476137675a6e5a3348744e77614c62796d6236646463476e3257744e376e6859485667343733796f6d6770225d2c226465736372697074696f6e223a2254656d706f72616c2d66756e64696e6720546f6b656e20666f7220746865205465737420626f756e74792070726f6a6563742e20506c656173652c2065786368616e6765207468652041505420666f72207468652070726f6a65637420746f6b656e206f6e20426f756e746966756c206f6e63652074686520646561646c696e6520686173207061737365642e227d"
        },
        "R4": {
          "serializedValue": "0400",
          "sigmaType": "SInt",
          "renderedValue": "0"
        }
      }
    },
    {
      "boxId": "3d2cb69afbeb6cec824e661cc6ca4e6260de7ec121bbfc77be7886f0210920b8",
      "value": 1920522400,
      "index": 1,
      "spendingProof": "b6356995210b5b13bed693f0523a957cceab78d4a6cb71b3fb7408e1cbc09e640347dee6c4dba2036ccf803ef1b01699ec35e1775058b07d",
      "outputBlockId": "86a9d0216829ada4a631df7458008f22cef53937418a6fb440852035fe5a18a7",
      "outputTransactionId": "773ec7fe11fef5df3907419fbe03673e7fa2a1ef4648f608b3dd1a950f3abf27",
      "outputIndex": 2,
      "outputGlobalIndex": 49476636,
      "outputCreatedAt": 1591171,
      "outputSettledAt": 1591172,
      "ergoTree": "0008cd037997278992e996c5af9c4085e339b4224749113d748d39f3fd5295c68aae3fbb",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(799727,a7f755,...)))}",
      "address": "9hPMZDMrGa7gZnZ3HtNwaLbymb6ddcGn2WtN7nhYHVg473yomgp",
      "assets": [
        {
          "tokenId": "30974274078845f263b4f21787e33cc99e9ec19a17ad85a5bc6da2cca91c5a2e",
          "index": 0,
          "amount": 50000000000,
          "name": "WT_ADA",
          "decimals": 8,
          "type": "EIP-004"
        },
        {
          "tokenId": "ef802b475c06189fdbf844153cdc1d449a5ba87cce13d11bb47b5a539f27f12b",
          "index": 1,
          "amount": 25000000000,
          "name": "WT_ERG",
          "decimals": 9,
          "type": "EIP-004"
        },
        {
          "tokenId": "e91cbc48016eb390f8f872aa2962772863e2e840708517d1ab85e57451f91bed",
          "index": 2,
          "amount": 1200,
          "name": "Ergold",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "fbbaac7337d051c10fc3da0ccb864f4d32d40027551e1c3ea3ce361f39b91e40",
          "index": 3,
          "amount": 1200,
          "name": "kushti",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "00b1e236b60b95c2c6f8007a9d89bc460fc9e78f98b09faec9449007b40bccf3",
          "index": 4,
          "amount": 350000,
          "name": "EGIO",
          "decimals": 4,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [],
  "outputs": [
    {
      "boxId": "6f0a5b20190c9dae2f3a64190b8dc76f2d24d48d6e42b1e5ffe1ba1bc019d37b",
      "transactionId": "7192f499e30291fc1d029c8f883432d4a2e706950d1f9bb5f12d3ed319542ccb",
      "blockId": "cb5a25b3c5fbe50376139cef9114ec428087a3c9eecff75bc915a1b23e30f1ad",
      "value": 1000000,
      "index": 0,
      "globalIndex": 49476654,
      "creationHeight": 1591172,
      "settlementHeight": 1591173,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 1\n5: 1\n6: true\n7: 2\n8: 1\n9: 1\n10: 2\n11: 2\n12: 0\n13: 1\n14: 0\n15: 1\n16: 0\n17: 1\n18: 0\n19: 1\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 127\n27: 3\n28: 2\n29: SigmaProp(ProveDlog(ECPoint(799727,a7f755,...)))\n30: 1\n31: 2\n32: 1\n33: 100\n34: Coll(18,-12,78,44,-63,108,-19,-63,-55,79,-111,-66,-54,50,-42,26,7,-29,-56,17,-123,119,4,29,-43,-102,-4,107,22,4,-93,55)\n35: 0\n36: 0\n37: 1\n38: 0\n39: 100\n40: true\n41: 1\n42: Coll(0,-79,-30,54,-74,11,-107,-62,-58,-8,0,122,-99,-119,-68,70,15,-55,-25,-113,-104,-80,-97,-82,-55,68,-112,7,-76,11,-52,-13)\n43: 2\n44: 0\n45: 0\n46: 1100000\n47: 0\n48: 1\n49: false\n50: 1\n51: 0\n52: 0\n53: 1\n54: 0\n55: 1100000\n56: 0\n57: true\n58: 1\n59: 1\n60: 0\n61: true\n62: true\n63: 1\n64: true",
      "ergoTreeScript": "{\n  val coll1 = SELF.tokens\n  val i2 = coll1.size\n  val bool3 = i2 == placeholder[Int](0)\n  val tuple4 = coll1(placeholder[Int](1))\n  val coll5 = tuple4._1\n  val box6 = OUTPUTS(placeholder[Int](2))\n  val coll7 = box6.tokens\n  val tuple8 = coll7(placeholder[Int](3))\n  val i9 = SELF.R4[Int].get\n  val l10 = SELF.R5[Long].get\n  val l11 = SELF.R7[Long].get\n  val bool12 = SELF.propositionBytes == box6.propositionBytes\n  val i13 = coll7.size\n  val bool14 = i13 == placeholder[Int](4)\n  val tuple15 = coll7(placeholder[Int](5))\n  val bool16 = (\n    (\n      (\n        (\n          ((((coll5 == tuple8._1) && (i9 == box6.R4[Int].get)) && (l10 == box6.R5[Long].get)) && (l11 == box6.R7[Long].get)) && (\n            SELF.R8[Coll[Byte]].get == box6.R8[Coll[Byte]].get\n          )\n        ) && (SELF.R9[Coll[Byte]].get == box6.R9[Coll[Byte]].get)\n      ) && bool12\n    ) && anyOf(Coll[Boolean](bool14, tuple15._1 == Coll[Byte](), placeholder[Boolean](6)))\n  ) && (bool14 || (i13 == placeholder[Int](7)))\n  val coll17 = SELF.R6[Coll[Long]].get\n  val l18 = coll17(placeholder[Int](8))\n  val coll19 = box6.R6[Coll[Long]].get\n  val l20 = coll19(placeholder[Int](9))\n  val bool21 = l18 == l20\n  val l22 = coll17(placeholder[Int](10))\n  val l23 = coll19(placeholder[Int](11))\n  val bool24 = l22 == l23\n  val l25 = tuple15._2\n  val bool26 = if (bool3) { placeholder[Long](12) } else { coll1(placeholder[Int](13))._2 } == if (bool14) { placeholder[Long](14) } else { l25 }\n  val l27 = tuple4._2\n  val l28 = tuple8._2\n  val l29 = l27 - l28\n  val l30 = {(box30: Box) =>\n    val coll32 = box30.tokens\n    val coll33 = box30.R6[Coll[Long]].get\n    if (coll32.size == placeholder[Int](15)) { placeholder[Long](16) } else { coll32(placeholder[Int](17))._2 } - coll33(placeholder[Int](18)) + coll33(\n      placeholder[Int](19)\n    ) + coll33(placeholder[Int](20))\n  }(SELF)\n  val l31 = box6.value\n  val l32 = SELF.value\n  val l33 = coll19(placeholder[Int](21))\n  val l34 = coll17(placeholder[Int](22))\n  val l35 = l33 - l34\n  val bool36 = l34 == l33\n  val l37 = l28 - l27\n  val l38 = l20 - l18\n  val l39 = l32 - l31\n  val l40 = if (bool12) { l39 } else { l32 }\n  val bool41 = l27 == l28\n  val bool42 = l34 >= l10\n  val func43 = {(tuple43: (SigmaProp, Box)) =>\n    val coll45 = tuple43._2.propositionBytes\n    val coll46 = tuple43._1.propBytes\n    if (coll45(placeholder[Int](23)).toInt == placeholder[Int](24)) { coll45 == coll46 } else {(\n      val i47 = coll45.size\n      coll46.slice(placeholder[Int](25), coll46.size) == coll45.slice(\n        if (i47 > placeholder[Int](26)) { placeholder[Int](27) } else { placeholder[Int](28) }, i47\n      )\n    )}\n  }\n  val prop44 = placeholder[SigmaProp](29)\n  val box45 = OUTPUTS(placeholder[Int](30))\n  val bool46 = func43((prop44, box45))\n  val box47 = OUTPUTS(placeholder[Int](31))\n  val i48 = placeholder[Int](32)\n  val l49 = l40 * i48.toLong / placeholder[Long](33)\n  val coll50 = placeholder[Coll[Byte]](34)\n  val bool51 = l32 == l31\n  val bool52 = allOf(Coll[Boolean](bool16, bool36, bool21, bool24, bool51, bool41))\n  val l53 = if (bool14) { placeholder[Long](35) } else { l25 } - if (bool3) { placeholder[Long](36) } else { coll1(placeholder[Int](37))._2 }\n  val l54 = !l53\n  val coll55 = CONTEXT.dataInputs\n  val prop56 = sigmaProp(proveDlog(coll55.filter({(box56: Box) =>\n          val opt58 = box56.R5[Coll[Byte]]\n          (opt58.isDefined && (opt58.get == coll5)) && box56.R4[GroupElement].isDefined\n        })(placeholder[Int](38)).R4[GroupElement].get))\n  val coll57 = OUTPUTS.filter({(box57: Box) => func43((prop56, box57)) })\n  val l58 = if (bool12) { l39 } else { l32 }\n  val l59 = l58 * i48.toLong / placeholder[Long](39)\n  sigmaProp(\n    if (bool3) { placeholder[Boolean](40) } else { coll1(placeholder[Int](41))._1 == placeholder[Coll[Byte]](42) } && (bool3 || (i2 == placeholder[Int](43)))\n  ) && sigmaProp(\n    anyOf(\n      Coll[Boolean](\n        allOf(\n          Coll[Boolean](\n            allOf(Coll[Boolean](bool16, bool21, bool24, bool26)), l29 <= l30, l31 - l32 == l29 * l11, allOf(\n              Coll[Boolean](l29 == l35, l35 > placeholder[Long](44))\n            )\n          )\n        ), allOf(\n          Coll[Boolean](\n            allOf(Coll[Boolean](bool16, bool36, bool24, bool26)), (HEIGHT > i9) && (l34 < l10), allOf(\n              Coll[Boolean](l37 == l38, l38 > placeholder[Long](45))\n            ), l39 == l37 * l11\n          )\n        ), allOf(\n          Coll[Boolean](\n            allOf(Coll[Boolean](bool16 || ((l40 == l32) && bool3), bool36, bool21, bool24, bool41, bool26)), bool42, bool46, allOf(\n              Coll[Boolean](box47.value == l49, coll50 == blake2b256(box47.propositionBytes))\n            ), box45.value == l40 - l49 - placeholder[Int](46).toLong\n          )\n        ), allOf(Coll[Boolean](bool52, bool46, l53 < placeholder[Long](47), l54 <= l30)), if (INPUTS.size == placeholder[Int](48)) {\n          placeholder[Boolean](49)\n        } else { allOf(Coll[Boolean](bool52, func43((prop44, INPUTS(placeholder[Int](50)))), l53 > placeholder[Long](51))) }, allOf(\n          Coll[Boolean](\n            allOf(Coll[Boolean](bool16 || (bool51 && bool3), bool36, bool21, bool51)), bool42, l37 == l23 - l22, allOf(\n              Coll[Boolean](l37 == l54, l37 > placeholder[Long](52))\n            )\n          )\n        )\n      )\n    )\n  ) || prop44 && sigmaProp(allOf(Coll[Boolean](bool42, coll55.exists({(box60: Box) =>\n            val opt62 = box60.R5[Coll[Byte]]\n            (opt62.isDefined && (opt62.get == coll5)) && box60.R4[GroupElement].isDefined\n          }), (coll57.size >= placeholder[Int](53)) && (coll57.map({(box60: Box) => box60.value }).fold(placeholder[Long](54), {(tuple60: (Long, Long)) => tuple60._1 + tuple60._2 }) >= l58 - l59 - placeholder[Long](55)), if (l59 > placeholder[Long](56)) { OUTPUTS.exists({(box60: Box) => (coll50 == blake2b256(box60.propositionBytes)) && (box60.value >= l59) }) } else { placeholder[Boolean](57) }, if (i2 > placeholder[Int](58)) {(\n          val tuple60 = coll1(placeholder[Int](59))\n          val l61 = tuple60._2 - l34\n          if (l61 > placeholder[Long](60)) { OUTPUTS.exists({(box62: Box) => func43((prop56, box62)) && box62.tokens.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == tuple60._1) && (tuple64._2 >= l61) }) }) } else { placeholder[Boolean](61) }\n        )} else { placeholder[Boolean](62) }, if ((l58 == l32) && (bool3 || (coll1(placeholder[Int](63))._2 <= l34))) { placeholder[Boolean](64) } else { (((bool16 && bool41) && bool36) && bool21) && bool24 })))\n}",
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      "assets": [
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          "type": "EIP-004"
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          "sigmaType": "SLong",
          "renderedValue": "0"
        },
        "R6": {
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          "sigmaType": "Coll[SLong]",
          "renderedValue": "[0,0,0]"
        },
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        "R7": {
          "serializedValue": "05c801",
          "sigmaType": "SLong",
          "renderedValue": "100"
        },
        "R9": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "7b227469746c65223a225465737420626f756e7479222c226465736372697074696f6e223a2274657374206465736372697074696f6e222c22696d616765223a22222c226c696e6b223a22222c226a7564676573223a5b223968504d5a444d72476137675a6e5a3348744e77614c62796d6236646463476e3257744e376e6859485667343733796f6d6770225d7d"
        },
        "R4": {
          "serializedValue": "04c6efc401",
          "sigmaType": "SInt",
          "renderedValue": "1612771"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "c088bd561f1c94e7793d084361584e2a760d30aa2463fafcc784ae737f5a6fc4",
      "transactionId": "7192f499e30291fc1d029c8f883432d4a2e706950d1f9bb5f12d3ed319542ccb",
      "blockId": "cb5a25b3c5fbe50376139cef9114ec428087a3c9eecff75bc915a1b23e30f1ad",
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      "index": 1,
      "globalIndex": 49476655,
      "creationHeight": 1591172,
      "settlementHeight": 1591173,
      "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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      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(799727,a7f755,...)))}",
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      "mainChain": true
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}