Ad
Inputs (2)
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.5433 ERG
Outputs (4)
Settlement height:
Value:
0.11 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent in transaction:
Settlement height:
Value:
0.4322 ERG
Transaction Details
Status: Confirmed
Size: 2.64 KB
Received time: 12/4/2025 03:47:34 PM
Included in blocks: 1,670,389
Confirmations: 100,926
Total coins transferred: 0.5533 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000406 ERG
Raw Transaction Data
{
  "id": "bec4ede877ec947c4e15f4d49e679acf1d87992cf1c52a2f31d2d865eb5b3cac",
  "blockId": "976cc99ebc0da46d47dc2478239a1e6fc2de283a9fc828ea32e8c25f6b8c43df",
  "inclusionHeight": 1670389,
  "timestamp": 1764863254993,
  "index": 15,
  "globalIndex": 9911269,
  "numConfirmations": 100926,
  "inputs": [
    {
      "boxId": "1c03e144fa4d2ec6ce71a74ee09e22dbff07690571fc4f29285c2d5e012961a2",
      "value": 10000000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "976cc99ebc0da46d47dc2478239a1e6fc2de283a9fc828ea32e8c25f6b8c43df",
      "outputTransactionId": "89b4747535498caf8740114d171f3c08f903d3a760dbfb70f6e7811b5d7bbd5c",
      "outputIndex": 0,
      "outputGlobalIndex": 52031193,
      "outputCreatedAt": 1670388,
      "outputSettledAt": 1670389,
      "ergoTree": "19de0f73040204000402040204000402040604000245025202470402040404000400040204020402040005000404040405020502040204020406040404060400040204040580dac4090580dac4090580dac409040204060406040404040580dac4090580dac4090580dac4090402010005020200020102020400040204000580dac4090500040604040500050004000500040004000402040002010200020204000402040405c8010500040204000500040004000502010104040502040204000400040004020402040404060580dac40904040580dac40904040580dac40904040580dac40904040400050008cd02e45f52ffb0ac1e95c5f61b2ad6a2232bb35322f504fff3bb53a28a66b2886302040204000400040204020400010105000500050005000400040001010100d814d601e4c6a70710d602b27201730000d6039ab272017301007202d604c2a7d60593b1b5a5d901056393c2720572047302d60693b1b5a4d901066393c2720672047303d607e4c6a70405d608db6308a7d6098cb2720873040001d60ab27208730500d60b8c720a01d60cb27201730600d60de4c6a70810d60ee4c6a70911d60fb2720e730700d610e4c6a7060ed61193721083030273087309730ad612e4c6a7050ed613b2720e730b00d614b27201730c00958fa37203d80dd615b2a5730d00d616db63087215d617b17216d618b27216730e00d619b27216730f00d61a8c721902d61b999a720c73107d721a04d61ce4c672150810d61db2a5731100d61ee4c6721d0402d61f7e721e04d620b2db6308721d731200d621c6721d060ed1edededededededededededededededed72067205917207731392b1a573149272177315ed938c7218017209938c7218027316ed938c721901720b93721a998c720a02731790721b720ceded93b2721c721f009ab2720d721f007318d801d6229e9a721f7319731a93b2721c722200b2720d722200d801d6229e9a721f731b731c93b2721c722200b2720d722200939a9ab2721c731d00b2721c731e00b2721c731f00721b957211d803d622c17215d623c1a7d6249999722273209972237321edededed927224720f9372229a7223722493c1721d732293b1db6308721d732393e4c6721d07057224d801d622ed92b1720873249272177325ed7222957222d805d623b27208732600d624b27216732700d6258c722402d6268c722302d6279972257226ededededededed938c7223017210938c7224017210927227720f9372259a72267227ed93c17215732893c1a7732993c1721d732a93b1db6308721d732b93e4c6721d07057227732cedededed93e4c672150405720793e4c67215050e721293e4c67215060e721093e4c672150710720193e4c672150911720e93c272157204ed938c722001720b938c722002732decec93721e732e93721e732f93721e7330e6c6721d050eede6722193e4722172099592a39a72037214d815d615b2db6501fe733100d616db63087215d617e4c672150405d618b5a4d9011863d801d61adb63087218ed92b1721a7332938cb2721a73330001720bd619b17218d61a957211d801d61a99c1a773348602721a93721a9ab072187335d9011b41639a8c721b01e4c68c721b02070572139592b172087336d801d61a8cb27208733700028602721a93721a9ab072187338d9011b41639a8c721b01e4c68c721b020705721386027339ed937219733a937213733bd61bb2a5733c00d61cdb6308721bd61db1721cd61eb2721c733d00d61fb2721c733e00d620e4c6721b0710d621b27220733f00d622b57218d901226393e4c6722204029591721772077340958f7217720773417342d62391b172227343d624e4c6721b0911d625b27224734400d6268c721a01d6279d9c72267e7345057346d6289972267227d6299172267347d1ededededededededededededededededed72067205ed92b172167348938cb27216734900017212917217734a8c721a0295917219734baf7218d9012a63d801d62cb2db6308722a734c00ededededed938c722c01720b938c722c02734de6c6722a0402e6c6722a050ee6c6722a060ee6c6722a0705734e92721d734fed938c721e017209938c721e027350ed938c721f01720b938c721f027e9a720c73510593e4c6721b0810830304735273537354ededededed93e4c6721b04057217ed927221a39072219aa3735593b27220735600720293b27220735700721493b27220735800720c93e4c6721b060e721093e4c6721b050e721293c2721b7204957223957211ed93c1721b735993721d735aed93c1721b735b93721d735c957211ed92c1721b9a735d722593721d735eed92c1721b9a735f722593721d736093b27224736100720f93722595722373627228957229d801d62ab5a5d9012a6393c2722ad07363957211ed92b1722a736492c1b2722a7365007227d801d62bb5db6308b2722a736600d9012b4d0e938c722b017210eded92b1722a736792b1722b7368928cb2722b736900027227736a95ed72237229af7222d9012a63d803d62ce4c6722a050ed62db5a5d9012d6393c2722d722cd62e9d9cb07222736bd9012e4163d802d6308c722e02d6318c722e019593e4c67230050e722c9a7231e4c67230070572317228b07222736cd9012e41639a8c722e01e4c68c722e02070595721192b0722d736dd9012f41639a8c722f01c18c722f02722e92b0722d736ed9012f4163d802d631b5db63088c722f02d901314d0e938c7231017210d6328c722f019591b17231736f9a72328cb27231737000027232722e7371d17372",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 1\n4: 0\n5: 1\n6: 3\n7: 0\n8: 69\n9: 82\n10: 71\n11: 1\n12: 2\n13: 0\n14: 0\n15: 1\n16: 1\n17: 1\n18: 0\n19: 0\n20: 2\n21: 2\n22: 1\n23: 1\n24: 1\n25: 1\n26: 3\n27: 2\n28: 3\n29: 0\n30: 1\n31: 2\n32: 10000000\n33: 10000000\n34: 10000000\n35: 1\n36: 3\n37: 3\n38: 2\n39: 2\n40: 10000000\n41: 10000000\n42: 10000000\n43: 1\n44: false\n45: 1\n46: 0\n47: 1\n48: 2\n49: 0\n50: 1\n51: 0\n52: 10000000\n53: 0\n54: 3\n55: 2\n56: 0\n57: 0\n58: 0\n59: 0\n60: 0\n61: 0\n62: 1\n63: 0\n64: 1\n65: 0\n66: 2\n67: 0\n68: 1\n69: 2\n70: 100\n71: 0\n72: 1\n73: 0\n74: 0\n75: 0\n76: 0\n77: 1\n78: true\n79: 2\n80: 1\n81: 1\n82: 0\n83: 0\n84: 0\n85: 1\n86: 1\n87: 2\n88: 3\n89: 10000000\n90: 2\n91: 10000000\n92: 2\n93: 10000000\n94: 2\n95: 10000000\n96: 2\n97: 0\n98: 0\n99: SigmaProp(ProveDlog(ECPoint(e45f52,5253a8,...)))\n100: 1\n101: 0\n102: 0\n103: 1\n104: 1\n105: 0\n106: true\n107: 0\n108: 0\n109: 0\n110: 0\n111: 0\n112: 0\n113: true\n114: false",
      "ergoTreeScript": "{\n  val coll1 = SELF.R7[Coll[Int]].get\n  val i2 = coll1(placeholder[Int](0))\n  val i3 = coll1(placeholder[Int](1)) + i2\n  val coll4 = SELF.propositionBytes\n  val bool5 = OUTPUTS.filter({(box5: Box) => box5.propositionBytes == coll4 }).size == placeholder[Int](2)\n  val bool6 = INPUTS.filter({(box6: Box) => box6.propositionBytes == coll4 }).size == placeholder[Int](3)\n  val l7 = SELF.R4[Long].get\n  val coll8 = SELF.tokens\n  val coll9 = coll8(placeholder[Int](4))._1\n  val tuple10 = coll8(placeholder[Int](5))\n  val coll11 = tuple10._1\n  val i12 = coll1(placeholder[Int](6))\n  val coll13 = SELF.R8[Coll[Int]].get\n  val coll14 = SELF.R9[Coll[Long]].get\n  val l15 = coll14(placeholder[Int](7))\n  val coll16 = SELF.R6[Coll[Byte]].get\n  val bool17 = coll16 == Coll[Byte](placeholder[Byte](8), placeholder[Byte](9), placeholder[Byte](10))\n  val coll18 = SELF.R5[Coll[Byte]].get\n  val l19 = coll14(placeholder[Int](11))\n  val i20 = coll1(placeholder[Int](12))\n  if (HEIGHT < i3) {(\n    val box21 = OUTPUTS(placeholder[Int](13))\n    val coll22 = box21.tokens\n    val i23 = coll22.size\n    val tuple24 = coll22(placeholder[Int](14))\n    val tuple25 = coll22(placeholder[Int](15))\n    val l26 = tuple25._2\n    val i27 = i12 + placeholder[Int](16) - l26.toInt\n    val coll28 = box21.R8[Coll[Int]].get\n    val box29 = OUTPUTS(placeholder[Int](17))\n    val b30 = box29.R4[Byte].get\n    val i31 = b30.toInt\n    val tuple32 = box29.tokens(placeholder[Int](18))\n    val opt33 = box29.R6[Coll[Byte]]\n    sigmaProp(\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (((bool6 && bool5) && (l7 > placeholder[Long](19))) && (OUTPUTS.size >= placeholder[Int](20))) && (i23 >= placeholder[Int](21))\n                            ) && ((tuple24._1 == coll9) && (tuple24._2 == placeholder[Long](22)))\n                          ) && ((tuple25._1 == coll11) && (l26 == tuple10._2 - placeholder[Long](23)))\n                        ) && (i27 <= i12)\n                      ) && (((coll28(i31) == coll13(i31) + placeholder[Int](24)) && \n                            val i34 = i31 + placeholder[Int](25) % placeholder[Int](26)\n                            coll28(i34) == coll13(i34)\n                          ) && \n                          val i34 = i31 + placeholder[Int](27) % placeholder[Int](28)\n                          coll28(i34) == coll13(i34)\n                        )\n                    ) && (coll28(placeholder[Int](29)) + coll28(placeholder[Int](30)) + coll28(placeholder[Int](31)) == i27)\n                  ) && if (bool17) {(\n                    val l34 = box21.value\n                    val l35 = SELF.value\n                    val l36 = l34 - placeholder[Long](32) - l35 - placeholder[Long](33)\n                    ((((l36 >= l15) && (l34 == l35 + l36)) && (box29.value == placeholder[Long](34))) && (box29.tokens.size == placeholder[Int](35))) && (\n                      box29.R7[Long].get == l36\n                    )\n                  )} else {(\n                    val bool34 = (coll8.size >= placeholder[Int](36)) && (i23 >= placeholder[Int](37))\n                    bool34 && if (bool34) {(\n                      val tuple35 = coll8(placeholder[Int](38))\n                      val tuple36 = coll22(placeholder[Int](39))\n                      val l37 = tuple36._2\n                      val l38 = tuple35._2\n                      val l39 = l37 - l38\n                      (\n                        (\n                          (\n                            ((((tuple35._1 == coll16) && (tuple36._1 == coll16)) && (l39 >= l15)) && (l37 == l38 + l39)) && (\n                              (box21.value == placeholder[Long](40)) && (SELF.value == placeholder[Long](41))\n                            )\n                          ) && (box29.value == placeholder[Long](42))\n                        ) && (box29.tokens.size == placeholder[Int](43))\n                      ) && (box29.R7[Long].get == l39)\n                    )} else { placeholder[Boolean](44) }\n                  )}\n                ) && (\n                  (\n                    (((box21.R4[Long].get == l7) && (box21.R5[Coll[Byte]].get == coll18)) && (box21.R6[Coll[Byte]].get == coll16)) && (\n                      box21.R7[Coll[Int]].get == coll1\n                    )\n                  ) && (box21.R9[Coll[Long]].get == coll14)\n                )\n              ) && (box21.propositionBytes == coll4)\n            ) && ((tuple32._1 == coll11) && (tuple32._2 == placeholder[Long](45)))\n          ) && (((b30 == placeholder[Byte](46)) || (b30 == placeholder[Byte](47))) || (b30 == placeholder[Byte](48)))\n        ) && box29.R5[Coll[Byte]].isDefined\n      ) && (opt33.isDefined && (opt33.get == coll9))\n    )\n  )} else { if (HEIGHT >= i3 + i20) {(\n      val box21 = CONTEXT.dataInputs(placeholder[Int](49))\n      val coll22 = box21.tokens\n      val l23 = box21.R4[Long].get\n      val coll24 = INPUTS.filter({(box24: Box) =>\n          val coll26 = box24.tokens\n          (coll26.size >= placeholder[Int](50)) && (coll26(placeholder[Int](51))._1 == coll11)\n        })\n      val i25 = coll24.size\n      val tuple26 = if (bool17) {(\n        val l26 = SELF.value - placeholder[Long](52)\n        (l26, l26 == coll24.fold(placeholder[Long](53), {(tuple27: (Long, Box)) => tuple27._1 + tuple27._2.R7[Long].get }) + l19)\n      )} else { if (coll8.size >= placeholder[Int](54)) {(\n          val l26 = coll8(placeholder[Int](55))._2\n          (l26, l26 == coll24.fold(placeholder[Long](56), {(tuple27: (Long, Box)) => tuple27._1 + tuple27._2.R7[Long].get }) + l19)\n        )} else { (placeholder[Long](57), (i25 == placeholder[Int](58)) && (l19 == placeholder[Long](59))) } }\n      val box27 = OUTPUTS(placeholder[Int](60))\n      val coll28 = box27.tokens\n      val i29 = coll28.size\n      val tuple30 = coll28(placeholder[Int](61))\n      val tuple31 = coll28(placeholder[Int](62))\n      val coll32 = box27.R7[Coll[Int]].get\n      val i33 = coll32(placeholder[Int](63))\n      val coll34 = coll24.filter({(box34: Box) => box34.R4[Byte].get == if (l23 > l7) { placeholder[Byte](64) } else { if (l23 < l7) { placeholder[Byte](65) } else { placeholder[Byte](66) } } })\n      val bool35 = coll34.size > placeholder[Int](67)\n      val coll36 = box27.R9[Coll[Long]].get\n      val l37 = coll36(placeholder[Int](68))\n      val l38 = tuple26._1\n      val l39 = l38 * placeholder[Int](69).toLong / placeholder[Long](70)\n      val l40 = l38 - l39\n      val bool41 = l38 > placeholder[Long](71)\n      sigmaProp(((((((((((((((((bool6 && bool5) && ((coll22.size >= placeholder[Int](72)) && (coll22(placeholder[Int](73))._1 == coll18))) && (l23 > placeholder[Long](74))) && tuple26._2) && if (i25 > placeholder[Int](75)) { coll24.forall({(box42: Box) =>\n                                      val tuple44 = box42.tokens(placeholder[Int](76))\n                                      (((((tuple44._1 == coll11) && (tuple44._2 == placeholder[Long](77))) && box42.R4[Byte].isDefined) && box42.R5[Coll[Byte]].isDefined) && box42.R6[Coll[Byte]].isDefined) && box42.R7[Long].isDefined\n                                    }) } else { placeholder[Boolean](78) }) && (i29 >= placeholder[Int](79))) && ((tuple30._1 == coll9) && (tuple30._2 == placeholder[Long](80)))) && ((tuple31._1 == coll11) && (tuple31._2 == i12 + placeholder[Int](81).toLong))) && (box27.R8[Coll[Int]].get == Coll[Int](placeholder[Int](82), placeholder[Int](83), placeholder[Int](84)))) && ((((((box27.R4[Long].get == l23) && ((i33 >= HEIGHT) && (i33 <= HEIGHT + placeholder[Int](85)))) && (coll32(placeholder[Int](86)) == i2)) && (coll32(placeholder[Int](87)) == i20)) && (coll32(placeholder[Int](88)) == i12)) && (box27.R6[Coll[Byte]].get == coll16))) && (box27.R5[Coll[Byte]].get == coll18)) && (box27.propositionBytes == coll4)) && if (bool35) { if (bool17) { (box27.value == placeholder[Long](89)) && (i29 == placeholder[Int](90)) } else { (box27.value == placeholder[Long](91)) && (i29 == placeholder[Int](92)) } } else { if (bool17) { (box27.value >= placeholder[Long](93) + l37) && (i29 == placeholder[Int](94)) } else { (box27.value >= placeholder[Long](95) + l37) && (i29 == placeholder[Int](96)) } }) && (coll36(placeholder[Int](97)) == l15)) && (l37 == if (bool35) { placeholder[Long](98) } else { l40 })) && if (bool41) {(\n            val coll42 = OUTPUTS.filter({(box42: Box) => box42.propositionBytes == placeholder[SigmaProp](99).propBytes })\n            if (bool17) { (coll42.size >= placeholder[Int](100)) && (coll42(placeholder[Int](101)).value >= l39) } else {(\n              val coll43 = coll42(placeholder[Int](102)).tokens.filter({(tuple43: (Coll[Byte], Long)) => tuple43._1 == coll16 })\n              ((coll42.size >= placeholder[Int](103)) && (coll43.size >= placeholder[Int](104))) && (coll43(placeholder[Int](105))._2 >= l39)\n            )}\n          )} else { placeholder[Boolean](106) }) && if (bool35 && bool41) { coll34.forall({(box42: Box) =>\n              val coll44 = box42.R5[Coll[Byte]].get\n              val coll45 = OUTPUTS.filter({(box45: Box) => box45.propositionBytes == coll44 })\n              val l46 = coll34.fold(placeholder[Long](107), {(tuple46: (Long, Box)) =>\n                  val box48 = tuple46._2\n                  val l49 = tuple46._1\n                  if (box48.R5[Coll[Byte]].get == coll44) { l49 + box48.R7[Long].get } else { l49 }\n                }) * l40 / coll34.fold(placeholder[Long](108), {(tuple46: (Long, Box)) => tuple46._1 + tuple46._2.R7[Long].get })\n              if (bool17) { coll45.fold(placeholder[Long](109), {(tuple47: (Long, Box)) => tuple47._1 + tuple47._2.value }) >= l46 } else { coll45.fold(placeholder[Long](110), {(tuple47: (Long, Box)) =>\n                    val coll49 = tuple47._2.tokens.filter({(tuple49: (Coll[Byte], Long)) => tuple49._1 == coll16 })\n                    val l50 = tuple47._1\n                    if (coll49.size > placeholder[Int](111)) { l50 + coll49(placeholder[Int](112))._2 } else { l50 }\n                  }) >= l46 }\n            }) } else { placeholder[Boolean](113) })\n    )} else { sigmaProp(placeholder[Boolean](114)) } }\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "f37015d552bdb497b03ff55f7f31fc40354513734e8d9e7f80b2faaaa635d0ef",
          "index": 0,
          "amount": 1,
          "name": " ",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "c727de0a6a1934ee88e91dad80e00bd8abfe80f847078b7af007951d6a3589c3",
          "index": 1,
          "amount": 11,
          "name": " ",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "0e206a2b821b5727e85beb5e78b4efb9f0250d59cd48481d2ded2c23e91ba1d07c66",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "6a2b821b5727e85beb5e78b4efb9f0250d59cd48481d2ded2c23e91ba1d07c66"
        },
        "R6": {
          "serializedValue": "0e03455247",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "455247"
        },
        "R8": {
          "serializedValue": "1003000000",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[0,0,0]"
        },
        "R7": {
          "serializedValue": "1004eaf3cb010a0a14",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[1670389,5,5,10]"
        },
        "R9": {
          "serializedValue": "11028084af5f00",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000,0]"
        },
        "R4": {
          "serializedValue": "05d8e9f4d90e",
          "sigmaType": "SLong",
          "renderedValue": "1973328492"
        }
      }
    },
    {
      "boxId": "145fdcb1efe15c1847e471d0bd9874d98395cd4eda057e56fe0d7dddcfd63ef0",
      "value": 543300000,
      "index": 1,
      "spendingProof": "02845836e73a74d7040be32ec8643fca70f03c31f59b9305b28963f1bafdbc9a30055729d70e76446a8ffc0ef9b805e5575c5d22fbabad20",
      "outputBlockId": "661851170322a38881c2b081dddecb5f6dcdd829d2189b0a74498b0f7b1bae04",
      "outputTransactionId": "e31c385bc8d249d1d7782a880c2faf006af0ee5155c7baa51a248e8c7bf51892",
      "outputIndex": 3,
      "outputGlobalIndex": 52030133,
      "outputCreatedAt": 1670352,
      "outputSettledAt": 1670353,
      "ergoTree": "0008cd03848b1c77c1a24096d22ef8a8f78f4d97a5f411ff2d89138bc8bdca2cbac600b2",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(848b1c,dd161b,...)))}",
      "address": "9hUBLNSpZWLngoKBCUMpR6cG28UEJ97ogcsw2AJDNF47BBdycTR",
      "assets": [],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [],
  "outputs": [
    {
      "boxId": "04d6560e6e5f51f2c235794dcfdaa03a5dc9d5fa411135830353f99a4e1c76dc",
      "transactionId": "bec4ede877ec947c4e15f4d49e679acf1d87992cf1c52a2f31d2d865eb5b3cac",
      "blockId": "976cc99ebc0da46d47dc2478239a1e6fc2de283a9fc828ea32e8c25f6b8c43df",
      "value": 110000000,
      "index": 0,
      "globalIndex": 52031239,
      "creationHeight": 1670388,
      "settlementHeight": 1670389,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 1\n4: 0\n5: 1\n6: 3\n7: 0\n8: 69\n9: 82\n10: 71\n11: 1\n12: 2\n13: 0\n14: 0\n15: 1\n16: 1\n17: 1\n18: 0\n19: 0\n20: 2\n21: 2\n22: 1\n23: 1\n24: 1\n25: 1\n26: 3\n27: 2\n28: 3\n29: 0\n30: 1\n31: 2\n32: 10000000\n33: 10000000\n34: 10000000\n35: 1\n36: 3\n37: 3\n38: 2\n39: 2\n40: 10000000\n41: 10000000\n42: 10000000\n43: 1\n44: false\n45: 1\n46: 0\n47: 1\n48: 2\n49: 0\n50: 1\n51: 0\n52: 10000000\n53: 0\n54: 3\n55: 2\n56: 0\n57: 0\n58: 0\n59: 0\n60: 0\n61: 0\n62: 1\n63: 0\n64: 1\n65: 0\n66: 2\n67: 0\n68: 1\n69: 2\n70: 100\n71: 0\n72: 1\n73: 0\n74: 0\n75: 0\n76: 0\n77: 1\n78: true\n79: 2\n80: 1\n81: 1\n82: 0\n83: 0\n84: 0\n85: 1\n86: 1\n87: 2\n88: 3\n89: 10000000\n90: 2\n91: 10000000\n92: 2\n93: 10000000\n94: 2\n95: 10000000\n96: 2\n97: 0\n98: 0\n99: SigmaProp(ProveDlog(ECPoint(e45f52,5253a8,...)))\n100: 1\n101: 0\n102: 0\n103: 1\n104: 1\n105: 0\n106: true\n107: 0\n108: 0\n109: 0\n110: 0\n111: 0\n112: 0\n113: true\n114: false",
      "ergoTreeScript": "{\n  val coll1 = SELF.R7[Coll[Int]].get\n  val i2 = coll1(placeholder[Int](0))\n  val i3 = coll1(placeholder[Int](1)) + i2\n  val coll4 = SELF.propositionBytes\n  val bool5 = OUTPUTS.filter({(box5: Box) => box5.propositionBytes == coll4 }).size == placeholder[Int](2)\n  val bool6 = INPUTS.filter({(box6: Box) => box6.propositionBytes == coll4 }).size == placeholder[Int](3)\n  val l7 = SELF.R4[Long].get\n  val coll8 = SELF.tokens\n  val coll9 = coll8(placeholder[Int](4))._1\n  val tuple10 = coll8(placeholder[Int](5))\n  val coll11 = tuple10._1\n  val i12 = coll1(placeholder[Int](6))\n  val coll13 = SELF.R8[Coll[Int]].get\n  val coll14 = SELF.R9[Coll[Long]].get\n  val l15 = coll14(placeholder[Int](7))\n  val coll16 = SELF.R6[Coll[Byte]].get\n  val bool17 = coll16 == Coll[Byte](placeholder[Byte](8), placeholder[Byte](9), placeholder[Byte](10))\n  val coll18 = SELF.R5[Coll[Byte]].get\n  val l19 = coll14(placeholder[Int](11))\n  val i20 = coll1(placeholder[Int](12))\n  if (HEIGHT < i3) {(\n    val box21 = OUTPUTS(placeholder[Int](13))\n    val coll22 = box21.tokens\n    val i23 = coll22.size\n    val tuple24 = coll22(placeholder[Int](14))\n    val tuple25 = coll22(placeholder[Int](15))\n    val l26 = tuple25._2\n    val i27 = i12 + placeholder[Int](16) - l26.toInt\n    val coll28 = box21.R8[Coll[Int]].get\n    val box29 = OUTPUTS(placeholder[Int](17))\n    val b30 = box29.R4[Byte].get\n    val i31 = b30.toInt\n    val tuple32 = box29.tokens(placeholder[Int](18))\n    val opt33 = box29.R6[Coll[Byte]]\n    sigmaProp(\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (((bool6 && bool5) && (l7 > placeholder[Long](19))) && (OUTPUTS.size >= placeholder[Int](20))) && (i23 >= placeholder[Int](21))\n                            ) && ((tuple24._1 == coll9) && (tuple24._2 == placeholder[Long](22)))\n                          ) && ((tuple25._1 == coll11) && (l26 == tuple10._2 - placeholder[Long](23)))\n                        ) && (i27 <= i12)\n                      ) && (((coll28(i31) == coll13(i31) + placeholder[Int](24)) && \n                            val i34 = i31 + placeholder[Int](25) % placeholder[Int](26)\n                            coll28(i34) == coll13(i34)\n                          ) && \n                          val i34 = i31 + placeholder[Int](27) % placeholder[Int](28)\n                          coll28(i34) == coll13(i34)\n                        )\n                    ) && (coll28(placeholder[Int](29)) + coll28(placeholder[Int](30)) + coll28(placeholder[Int](31)) == i27)\n                  ) && if (bool17) {(\n                    val l34 = box21.value\n                    val l35 = SELF.value\n                    val l36 = l34 - placeholder[Long](32) - l35 - placeholder[Long](33)\n                    ((((l36 >= l15) && (l34 == l35 + l36)) && (box29.value == placeholder[Long](34))) && (box29.tokens.size == placeholder[Int](35))) && (\n                      box29.R7[Long].get == l36\n                    )\n                  )} else {(\n                    val bool34 = (coll8.size >= placeholder[Int](36)) && (i23 >= placeholder[Int](37))\n                    bool34 && if (bool34) {(\n                      val tuple35 = coll8(placeholder[Int](38))\n                      val tuple36 = coll22(placeholder[Int](39))\n                      val l37 = tuple36._2\n                      val l38 = tuple35._2\n                      val l39 = l37 - l38\n                      (\n                        (\n                          (\n                            ((((tuple35._1 == coll16) && (tuple36._1 == coll16)) && (l39 >= l15)) && (l37 == l38 + l39)) && (\n                              (box21.value == placeholder[Long](40)) && (SELF.value == placeholder[Long](41))\n                            )\n                          ) && (box29.value == placeholder[Long](42))\n                        ) && (box29.tokens.size == placeholder[Int](43))\n                      ) && (box29.R7[Long].get == l39)\n                    )} else { placeholder[Boolean](44) }\n                  )}\n                ) && (\n                  (\n                    (((box21.R4[Long].get == l7) && (box21.R5[Coll[Byte]].get == coll18)) && (box21.R6[Coll[Byte]].get == coll16)) && (\n                      box21.R7[Coll[Int]].get == coll1\n                    )\n                  ) && (box21.R9[Coll[Long]].get == coll14)\n                )\n              ) && (box21.propositionBytes == coll4)\n            ) && ((tuple32._1 == coll11) && (tuple32._2 == placeholder[Long](45)))\n          ) && (((b30 == placeholder[Byte](46)) || (b30 == placeholder[Byte](47))) || (b30 == placeholder[Byte](48)))\n        ) && box29.R5[Coll[Byte]].isDefined\n      ) && (opt33.isDefined && (opt33.get == coll9))\n    )\n  )} else { if (HEIGHT >= i3 + i20) {(\n      val box21 = CONTEXT.dataInputs(placeholder[Int](49))\n      val coll22 = box21.tokens\n      val l23 = box21.R4[Long].get\n      val coll24 = INPUTS.filter({(box24: Box) =>\n          val coll26 = box24.tokens\n          (coll26.size >= placeholder[Int](50)) && (coll26(placeholder[Int](51))._1 == coll11)\n        })\n      val i25 = coll24.size\n      val tuple26 = if (bool17) {(\n        val l26 = SELF.value - placeholder[Long](52)\n        (l26, l26 == coll24.fold(placeholder[Long](53), {(tuple27: (Long, Box)) => tuple27._1 + tuple27._2.R7[Long].get }) + l19)\n      )} else { if (coll8.size >= placeholder[Int](54)) {(\n          val l26 = coll8(placeholder[Int](55))._2\n          (l26, l26 == coll24.fold(placeholder[Long](56), {(tuple27: (Long, Box)) => tuple27._1 + tuple27._2.R7[Long].get }) + l19)\n        )} else { (placeholder[Long](57), (i25 == placeholder[Int](58)) && (l19 == placeholder[Long](59))) } }\n      val box27 = OUTPUTS(placeholder[Int](60))\n      val coll28 = box27.tokens\n      val i29 = coll28.size\n      val tuple30 = coll28(placeholder[Int](61))\n      val tuple31 = coll28(placeholder[Int](62))\n      val coll32 = box27.R7[Coll[Int]].get\n      val i33 = coll32(placeholder[Int](63))\n      val coll34 = coll24.filter({(box34: Box) => box34.R4[Byte].get == if (l23 > l7) { placeholder[Byte](64) } else { if (l23 < l7) { placeholder[Byte](65) } else { placeholder[Byte](66) } } })\n      val bool35 = coll34.size > placeholder[Int](67)\n      val coll36 = box27.R9[Coll[Long]].get\n      val l37 = coll36(placeholder[Int](68))\n      val l38 = tuple26._1\n      val l39 = l38 * placeholder[Int](69).toLong / placeholder[Long](70)\n      val l40 = l38 - l39\n      val bool41 = l38 > placeholder[Long](71)\n      sigmaProp(((((((((((((((((bool6 && bool5) && ((coll22.size >= placeholder[Int](72)) && (coll22(placeholder[Int](73))._1 == coll18))) && (l23 > placeholder[Long](74))) && tuple26._2) && if (i25 > placeholder[Int](75)) { coll24.forall({(box42: Box) =>\n                                      val tuple44 = box42.tokens(placeholder[Int](76))\n                                      (((((tuple44._1 == coll11) && (tuple44._2 == placeholder[Long](77))) && box42.R4[Byte].isDefined) && box42.R5[Coll[Byte]].isDefined) && box42.R6[Coll[Byte]].isDefined) && box42.R7[Long].isDefined\n                                    }) } else { placeholder[Boolean](78) }) && (i29 >= placeholder[Int](79))) && ((tuple30._1 == coll9) && (tuple30._2 == placeholder[Long](80)))) && ((tuple31._1 == coll11) && (tuple31._2 == i12 + placeholder[Int](81).toLong))) && (box27.R8[Coll[Int]].get == Coll[Int](placeholder[Int](82), placeholder[Int](83), placeholder[Int](84)))) && ((((((box27.R4[Long].get == l23) && ((i33 >= HEIGHT) && (i33 <= HEIGHT + placeholder[Int](85)))) && (coll32(placeholder[Int](86)) == i2)) && (coll32(placeholder[Int](87)) == i20)) && (coll32(placeholder[Int](88)) == i12)) && (box27.R6[Coll[Byte]].get == coll16))) && (box27.R5[Coll[Byte]].get == coll18)) && (box27.propositionBytes == coll4)) && if (bool35) { if (bool17) { (box27.value == placeholder[Long](89)) && (i29 == placeholder[Int](90)) } else { (box27.value == placeholder[Long](91)) && (i29 == placeholder[Int](92)) } } else { if (bool17) { (box27.value >= placeholder[Long](93) + l37) && (i29 == placeholder[Int](94)) } else { (box27.value >= placeholder[Long](95) + l37) && (i29 == placeholder[Int](96)) } }) && (coll36(placeholder[Int](97)) == l15)) && (l37 == if (bool35) { placeholder[Long](98) } else { l40 })) && if (bool41) {(\n            val coll42 = OUTPUTS.filter({(box42: Box) => box42.propositionBytes == placeholder[SigmaProp](99).propBytes })\n            if (bool17) { (coll42.size >= placeholder[Int](100)) && (coll42(placeholder[Int](101)).value >= l39) } else {(\n              val coll43 = coll42(placeholder[Int](102)).tokens.filter({(tuple43: (Coll[Byte], Long)) => tuple43._1 == coll16 })\n              ((coll42.size >= placeholder[Int](103)) && (coll43.size >= placeholder[Int](104))) && (coll43(placeholder[Int](105))._2 >= l39)\n            )}\n          )} else { placeholder[Boolean](106) }) && if (bool35 && bool41) { coll34.forall({(box42: Box) =>\n              val coll44 = box42.R5[Coll[Byte]].get\n              val coll45 = OUTPUTS.filter({(box45: Box) => box45.propositionBytes == coll44 })\n              val l46 = coll34.fold(placeholder[Long](107), {(tuple46: (Long, Box)) =>\n                  val box48 = tuple46._2\n                  val l49 = tuple46._1\n                  if (box48.R5[Coll[Byte]].get == coll44) { l49 + box48.R7[Long].get } else { l49 }\n                }) * l40 / coll34.fold(placeholder[Long](108), {(tuple46: (Long, Box)) => tuple46._1 + tuple46._2.R7[Long].get })\n              if (bool17) { coll45.fold(placeholder[Long](109), {(tuple47: (Long, Box)) => tuple47._1 + tuple47._2.value }) >= l46 } else { coll45.fold(placeholder[Long](110), {(tuple47: (Long, Box)) =>\n                    val coll49 = tuple47._2.tokens.filter({(tuple49: (Coll[Byte], Long)) => tuple49._1 == coll16 })\n                    val l50 = tuple47._1\n                    if (coll49.size > placeholder[Int](111)) { l50 + coll49(placeholder[Int](112))._2 } else { l50 }\n                  }) >= l46 }\n            }) } else { placeholder[Boolean](113) })\n    )} else { sigmaProp(placeholder[Boolean](114)) } }\n}",
      "address": "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",
      "assets": [
        {
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        },
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          "sigmaType": "Coll[SInt]",
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        },
        "R9": {
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        },
        "R4": {
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          "sigmaType": "SLong",
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        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
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      "index": 1,
      "globalIndex": 52031240,
      "creationHeight": 1670388,
      "settlementHeight": 1670389,
      "ergoTree": "19a7010d0402040004020100040002000201020204000402040004020404d802d601b5a4d9010163d801d603db63087201ed92b172037300938cb2720373010001e4c6a7060ed602e4c6a7040295ef93b172017302d17303d802d603b27201730400d604e4c672030710d1ededecec937202730593720273069372027307938cb2db6308a7730800018cb2db630872037309000192a39a9ab27204730a00b27204730b00b27204730c00",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: false\n4: 0\n5: 0\n6: 1\n7: 2\n8: 0\n9: 1\n10: 0\n11: 1\n12: 2",
      "ergoTreeScript": "{\n  val coll1 = INPUTS.filter({(box1: Box) =>\n      val coll3 = box1.tokens\n      (coll3.size >= placeholder[Int](0)) && (coll3(placeholder[Int](1))._1 == SELF.R6[Coll[Byte]].get)\n    })\n  val b2 = SELF.R4[Byte].get\n  if (!(coll1.size == placeholder[Int](2))) { sigmaProp(placeholder[Boolean](3)) } else {(\n    val box3 = coll1(placeholder[Int](4))\n    val coll4 = box3.R7[Coll[Int]].get\n    sigmaProp(\n      (\n        (((b2 == placeholder[Byte](5)) || (b2 == placeholder[Byte](6))) || (b2 == placeholder[Byte](7))) && (\n          SELF.tokens(placeholder[Int](8))._1 == box3.tokens(placeholder[Int](9))._1\n        )\n      ) && (HEIGHT >= coll4(placeholder[Int](10)) + coll4(placeholder[Int](11)) + coll4(placeholder[Int](12)))\n    )\n  )}\n}",
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      "assets": [
        {
          "tokenId": "c727de0a6a1934ee88e91dad80e00bd8abfe80f847078b7af007951d6a3589c3",
          "index": 0,
          "amount": 1,
          "name": " ",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0200",
          "sigmaType": "SByte",
          "renderedValue": "0"
        },
        "R5": {
          "serializedValue": "0e240008cd03848b1c77c1a24096d22ef8a8f78f4d97a5f411ff2d89138bc8bdca2cbac600b2",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd03848b1c77c1a24096d22ef8a8f78f4d97a5f411ff2d89138bc8bdca2cbac600b2"
        },
        "R6": {
          "serializedValue": "0e20f37015d552bdb497b03ff55f7f31fc40354513734e8d9e7f80b2faaaa635d0ef",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "f37015d552bdb497b03ff55f7f31fc40354513734e8d9e7f80b2faaaa635d0ef"
        },
        "R7": {
          "serializedValue": "058084af5f",
          "sigmaType": "SLong",
          "renderedValue": "100000000"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "e3c76ef50482ce1aaefa8f97ac47b5875c5c630233b070246c87905298f1cff8",
      "transactionId": "bec4ede877ec947c4e15f4d49e679acf1d87992cf1c52a2f31d2d865eb5b3cac",
      "blockId": "976cc99ebc0da46d47dc2478239a1e6fc2de283a9fc828ea32e8c25f6b8c43df",
      "value": 1100000,
      "index": 2,
      "globalIndex": 52031241,
      "creationHeight": 1670388,
      "settlementHeight": 1670389,
      "ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
      "ergoTreeScript": "{sigmaProp(\n  allOf(\n    Coll[Boolean](\n      HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n        placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n      ), OUTPUTS.size == placeholder[Int](4)\n    )\n  )\n)}",
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      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "71d5216a06ac503dbc16758f2f669cad6f167b75a7eb1f1b743749ed6cb94030",
      "mainChain": true
    },
    {
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      "value": 432200000,
      "index": 3,
      "globalIndex": 52031242,
      "creationHeight": 1670388,
      "settlementHeight": 1670389,
      "ergoTree": "0008cd03848b1c77c1a24096d22ef8a8f78f4d97a5f411ff2d89138bc8bdca2cbac600b2",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(848b1c,dd161b,...)))}",
      "address": "9hUBLNSpZWLngoKBCUMpR6cG28UEJ97ogcsw2AJDNF47BBdycTR",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "9b5873e6cecb67393c39d50e8c989e1d1659aaccae473d2b87ba4e0ec33ec453",
      "mainChain": true
    }
  ],
  "size": 2707,
  "isUnconfirmed": false
}