Ad
Inputs (3)
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
29.84 ERG
Tokens:
Loading assets...
Outputs (4)
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
125,136.73
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent in transaction:
Settlement height:
Value:
29.83 ERG
Tokens:
Loading assets...
Transaction Details
Status: Confirmed
Size: 5.23 KB
Received time: 4/8/2023 07:32:58 AM
Included in blocks: 977,844
Confirmations: 794,386
Total coins transferred: 29.84 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000187 ERG
Raw Transaction Data
{
  "id": "7c098e105519cb15bef75d0b04aa0a1ea7dbae32096ec36bdb4c47eac77edbed",
  "blockId": "a9c15d7076f8fcb08fd756f485bff5e1e3edb28064f063f3931033746aa2e4b9",
  "inclusionHeight": 977844,
  "timestamp": 1680939178758,
  "index": 2,
  "globalIndex": 5014531,
  "numConfirmations": 794386,
  "inputs": [
    {
      "boxId": "e798a550b83eac72122b0f12df4a170d0eaf41db056e580acab4803a1ca82519",
      "value": 1000000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "3aae4e8378ff90764aa6532e50566c390ec6a6586b54008acac4e2fd4a2b1b54",
      "outputTransactionId": "9c66783a6f20bd13cf60cc426f79f98ff902e3fb4b76fe9a28b8810f04200a0a",
      "outputIndex": 0,
      "outputGlobalIndex": 28094277,
      "outputCreatedAt": 977838,
      "outputSettledAt": 977840,
      "ergoTree": "1063040204000402040004020e20d71693c49a84fbbecd4908c94813b46514b18b67a99952dc1e6e4791556de4130400040004080408040404020402040404000400040004020404040405020406040605020e2025b7486b1a78647ad7d50a287e5e958b4e452a4bc86938c94218d706bc377ff0040004020580dddb01050205d00f04020502040204000e200d01f2f0b3254b4a1731e1b61ad77641fe54de2bd68d1c6fc1ae4e7e9ddfb212040604040402040604000e200549ea3374a36b7a22a803766af732e61798463c3332c5f6d86c8ab9195eed590402050204040500040205020404040404060400040004060500040004020400040005fdbfa8ca9a3a0402048090e4c00405100500050c050a05c801050805fa0105d00f0504052805c801053205c8010404040004020402050005000500040204040404050205000406040605020500050004040400040205d00f0400040201010100d816d601b2a5730000d602db63087201d603b27202730100d6048c720301d605db6308a7d606b27205730200d6078c720601d6089372047207d609b2a5730300d60ae4c672090411d60be4c6a70411d60c8c720602d60ddb63087209d60eb2720d730400d60f8c720e02d610db6903db6503fed6118c720302d6127305d613b2720d730600d614b27205730700d615b2720b730800d6169683070193c27209c2a793c17209c1a7938c7213018c721401938c7213028c721402938c720e01720793b2720a730900721593b1720d730a957208d807d617b27202730b00d6188c721702d619b2720b730c00d61ae4c672010411d61be4c67201050ed61cb2a5730d00d61db2db6308721c730e00d196831101721693b2720a730f009ab2720b731000721893b2720a731100721993b2720a7312009ab2720b731300731493b2720a731500b2720b73160093720f99720c731793cbc27201731893b2721a731900721992b2721a731a00997210731b93721bc5a77208937211731c938c7217017212927218731d93c2721cc2b2a4731e00938c721d01721b938c721d02731fd804d617b2a4732000d618db63087217d619b27218732100d61a8c72190195ed93721a732292b1a47323d804d61bb2a4732400d61ce4c6721b0411d61db2720b732500d61eb2720a732600d1968309017216938cb2db6308721b73270001732893b2721c73290099721d732a93b2721c732b00732c93b2720a732d009a721d732e93b2720a732f00b2720b73300093721e9ab2720b73310072158f721e721093720f720cd802d61bb2720b733200d61cb2720a73330095ed91721b721c92b1a47334d80fd61dd9011d0c63b0721d7335d9011f4163d802d621db63088c721f02d6228c721f019593b1722173367222d802d623b57221d901234d0e938c7223017212d624b172239593722473379a72228cb27223733800029593722473397222733ad61eda721d01a4d61fda721d01a5d620e4c672170411d621b27220733b00d6229d99721072217e733c05d62399721b721cd62495927222733d733e95927222733f9d9c7223734073419592722273429d9c7223734373449592722273459d9c7223734673479d9c722373487349d625b2a4734a00d626b27220734b00d627b2720b734c00d628b27218734d00d629998c7228027223d62a937229734ed62b8c722801d196830f0191721e734f91721f73509399721e721f72247216aedb63087225d9012c4d0e938c722c01e4c67217050e937226722793721c99721b722393b2720a735100722793b2720a73520099b2720b73530095722a7354735593b2720a735600b2720b73570093720f9a720c95722a7358735993c27201c27225937204722b937211997223722495917229735ad805d62cb2a5735b00d62ddb6308722cd62eb2722d735c00d62fb2722d735d00d630e4c6722c04119683080193c1722cc17217938c722e01721a938c722e028c721902938c722f01722b938c722f027229927229735e93b27230735f00722693b2723073600072217361d17362",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 0\n4: 1\n5: Coll(-41,22,-109,-60,-102,-124,-5,-66,-51,73,8,-55,72,19,-76,101,20,-79,-117,103,-87,-103,82,-36,30,110,71,-111,85,109,-28,19)\n6: 0\n7: 0\n8: 4\n9: 4\n10: 2\n11: 1\n12: 1\n13: 2\n14: 0\n15: 0\n16: 0\n17: 1\n18: 2\n19: 2\n20: 1\n21: 3\n22: 3\n23: 1\n24: Coll(37,-73,72,107,26,120,100,122,-41,-43,10,40,126,94,-107,-117,78,69,42,75,-56,105,56,-55,66,24,-41,6,-68,55,127,-16)\n25: 0\n26: 1\n27: 1800000\n28: 1\n29: 1000\n30: 1\n31: 1\n32: 1\n33: 0\n34: Coll(13,1,-14,-16,-77,37,75,74,23,49,-31,-74,26,-41,118,65,-2,84,-34,43,-42,-115,28,111,-63,-82,78,126,-99,-33,-78,18)\n35: 3\n36: 2\n37: 1\n38: 3\n39: 0\n40: Coll(5,73,-22,51,116,-93,107,122,34,-88,3,118,106,-9,50,-26,23,-104,70,60,51,50,-59,-10,-40,108,-118,-71,25,94,-19,89)\n41: 1\n42: 1\n43: 2\n44: 0\n45: 1\n46: 1\n47: 2\n48: 2\n49: 3\n50: 0\n51: 0\n52: 3\n53: 0\n54: 0\n55: 1\n56: 0\n57: 0\n58: -999999999999\n59: 1\n60: 604800000\n61: 8\n62: 0\n63: 6\n64: 5\n65: 100\n66: 4\n67: 125\n68: 1000\n69: 2\n70: 20\n71: 100\n72: 25\n73: 100\n74: 2\n75: 0\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 1\n82: 2\n83: 2\n84: 1\n85: 0\n86: 3\n87: 3\n88: 1\n89: 0\n90: 0\n91: 2\n92: 0\n93: 1\n94: 1000\n95: 0\n96: 1\n97: true\n98: false",
      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val tuple3 = coll2(placeholder[Int](1))\n  val coll4 = tuple3._1\n  val coll5 = SELF.tokens\n  val tuple6 = coll5(placeholder[Int](2))\n  val coll7 = tuple6._1\n  val bool8 = coll4 == coll7\n  val box9 = OUTPUTS(placeholder[Int](3))\n  val coll10 = box9.R4[Coll[Long]].get\n  val coll11 = SELF.R4[Coll[Long]].get\n  val l12 = tuple6._2\n  val coll13 = box9.tokens\n  val tuple14 = coll13(placeholder[Int](4))\n  val l15 = tuple14._2\n  val l16 = CONTEXT.preHeader.timestamp\n  val l17 = tuple3._2\n  val coll18 = placeholder[Coll[Byte]](5)\n  val tuple19 = coll13(placeholder[Int](6))\n  val tuple20 = coll5(placeholder[Int](7))\n  val l21 = coll11(placeholder[Int](8))\n  val bool22 = allOf(\n    Coll[Boolean](\n      box9.propositionBytes == SELF.propositionBytes, box9.value == SELF.value, tuple19._1 == tuple20._1, tuple19._2 == tuple20._2, tuple14._1 == coll7, coll10(\n        placeholder[Int](9)\n      ) == l21, coll13.size == placeholder[Int](10)\n    )\n  )\n  if (bool8) {(\n    val tuple23 = coll2(placeholder[Int](11))\n    val l24 = tuple23._2\n    val l25 = coll11(placeholder[Int](12))\n    val coll26 = box1.R4[Coll[Long]].get\n    val coll27 = box1.R5[Coll[Byte]].get\n    val box28 = OUTPUTS(placeholder[Int](13))\n    val tuple29 = box28.tokens(placeholder[Int](14))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          bool22, coll10(placeholder[Int](15)) == coll11(placeholder[Int](16)) + l24, coll10(placeholder[Int](17)) == l25, coll10(\n            placeholder[Int](18)\n          ) == coll11(placeholder[Int](19)) + placeholder[Long](20), coll10(placeholder[Int](21)) == coll11(placeholder[Int](22)), l15 == l12 - placeholder[\n            Long\n          ](23), blake2b256(box1.propositionBytes) == placeholder[Coll[Byte]](24), coll26(placeholder[Int](25)) == l25, coll26(\n            placeholder[Int](26)\n          ) >= l16 - placeholder[Long](27), coll27 == SELF.id, bool8, l17 == placeholder[Long](28), tuple23._1 == coll18, l24 >= placeholder[Long](\n            29\n          ), box28.propositionBytes == INPUTS(placeholder[Int](30)).propositionBytes, tuple29._1 == coll27, tuple29._2 == placeholder[Long](31)\n        )\n      )\n    )\n  )} else {(\n    val box23 = INPUTS(placeholder[Int](32))\n    val coll24 = box23.tokens\n    val tuple25 = coll24(placeholder[Int](33))\n    val coll26 = tuple25._1\n    if ((coll26 == placeholder[Coll[Byte]](34)) && (INPUTS.size >= placeholder[Int](35))) {(\n      val box27 = INPUTS(placeholder[Int](36))\n      val coll28 = box27.R4[Coll[Long]].get\n      val l29 = coll11(placeholder[Int](37))\n      val l30 = coll10(placeholder[Int](38))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            bool22, box27.tokens(placeholder[Int](39))._1 == placeholder[Coll[Byte]](40), coll28(placeholder[Int](41)) == l29 - placeholder[Long](42), coll28(\n              placeholder[Int](43)\n            ) == placeholder[Long](44), coll10(placeholder[Int](45)) == l29 + placeholder[Long](46), coll10(placeholder[Int](47)) == coll11(\n              placeholder[Int](48)\n            ), l30 == coll11(placeholder[Int](49)) + l21, l30 < l16, l15 == l12\n          )\n        )\n      )\n    )} else {(\n      val l27 = coll11(placeholder[Int](50))\n      val l28 = coll10(placeholder[Int](51))\n      if ((l27 > l28) && (INPUTS.size >= placeholder[Int](52))) {(\n        val func29 = {(coll29: Coll[Box]) => coll29.fold(placeholder[Long](53), {(tuple31: (Long, Box)) =>\n              val coll33 = tuple31._2.tokens\n              val l34 = tuple31._1\n              if (coll33.size == placeholder[Int](54)) { l34 } else {(\n                val coll35 = coll33.filter({(tuple35: (Coll[Byte], Long)) => tuple35._1 == coll18 })\n                val i36 = coll35.size\n                if (i36 == placeholder[Int](55)) { l34 + coll35(placeholder[Int](56))._2 } else { if (i36 == placeholder[Int](57)) { l34 } else { placeholder[Long](58) } }\n              )}\n            }) }\n        val l30 = func29(INPUTS)\n        val l31 = func29(OUTPUTS)\n        val coll32 = box23.R4[Coll[Long]].get\n        val l33 = coll32(placeholder[Int](59))\n        val l34 = l16 - l33 / placeholder[Int](60).toLong\n        val l35 = l27 - l28\n        val l36 = if (l34 >= placeholder[Long](61)) { placeholder[Long](62) } else {\n          if (l34 >= placeholder[Long](63)) { l35 * placeholder[Long](64) / placeholder[Long](65) } else {\n            if (l34 >= placeholder[Long](66)) { l35 * placeholder[Long](67) / placeholder[Long](68) } else {\n              if (l34 >= placeholder[Long](69)) { l35 * placeholder[Long](70) / placeholder[Long](71) } else {\n                l35 * placeholder[Long](72) / placeholder[Long](73)\n              }\n            }\n          }\n        }\n        val box37 = INPUTS(placeholder[Int](74))\n        val l38 = coll32(placeholder[Int](75))\n        val l39 = coll11(placeholder[Int](76))\n        val tuple40 = coll24(placeholder[Int](77))\n        val l41 = tuple40._2 - l35\n        val bool42 = l41 == placeholder[Long](78)\n        val coll43 = tuple40._1\n        sigmaProp(\n          allOf(\n            Coll[Boolean](\n              l30 > placeholder[Long](79), l31 > placeholder[Long](80), l30 - l31 == l36, bool22, box37.tokens.exists(\n                {(tuple44: (Coll[Byte], Long)) => tuple44._1 == box23.R5[Coll[Byte]].get }\n              ), l38 == l39, l28 == l27 - l35, coll10(placeholder[Int](81)) == l39, coll10(placeholder[Int](82)) == coll11(placeholder[Int](83)) - if (bool42) {\n                placeholder[Long](84)\n              } else { placeholder[Long](85) }, coll10(placeholder[Int](86)) == coll11(placeholder[Int](87)), l15 == l12 + if (bool42) {\n                placeholder[Long](88)\n              } else { placeholder[Long](89) }, box1.propositionBytes == box37.propositionBytes, coll4 == coll43, l17 == l35 - l36, if (l41 > placeholder[Long](\n                90\n              )) {(\n                val box44 = OUTPUTS(placeholder[Int](91))\n                val coll45 = box44.tokens\n                val tuple46 = coll45(placeholder[Int](92))\n                val tuple47 = coll45(placeholder[Int](93))\n                val coll48 = box44.R4[Coll[Long]].get\n                allOf(\n                  Coll[Boolean](\n                    box44.value == box23.value, tuple46._1 == coll26, tuple46._2 == tuple25._2, tuple47._1 == coll43, tuple47._2 == l41, l41 >= placeholder[\n                      Long\n                    ](94), coll48(placeholder[Int](95)) == l38, coll48(placeholder[Int](96)) == l33\n                  )\n                )\n              )} else { placeholder[Boolean](97) }\n            )\n          )\n        )\n      )} else { sigmaProp(placeholder[Boolean](98)) }\n    )}\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "05cde13424a7972fbcd0b43fccbb5e501b1f75302175178fc86d8f243f3f3125",
          "index": 0,
          "amount": 1,
          "name": "ergopad Stake State",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "1028de73d018f0c9a374b71555c5b8f1390994f2f41633e7b9d68f77735782ee",
          "index": 1,
          "amount": 999996538,
          "name": "ergopad Stake Token",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1105b8f2ebdb8601a8068c36c886f6d0eb6180f0b252",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[18081479836,404,3462,1680893460900,86400000]"
        }
      }
    },
    {
      "boxId": "c9705f9d23b6901b92653ee47d6e85d5650673cd426cf3627e576c5bf73ed645",
      "value": 1000000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "9b3a6c5edf4db23662c3c2dfd857b6d9b1b8e746f5f72ecc43b68b1e3643dae7",
      "outputTransactionId": "0a11bb6875824df2682da21429a392e7dbb240083c3c59fa9da84710012422e1",
      "outputIndex": 154,
      "outputGlobalIndex": 28082437,
      "outputCreatedAt": 977486,
      "outputSettledAt": 977488,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(5,73,-22,51,116,-93,107,122,34,-88,3,118,106,-9,50,-26,23,-104,70,60,51,50,-59,-10,-40,108,-118,-71,25,94,-19,89)\n3: 1\n4: 0\n5: 0\n6: 1\n7: 1\n8: 0\n9: 0\n10: 1\n11: 1\n12: 1\n13: 3\n14: 0\n15: 1\n16: 2\n17: Coll(5,-51,-31,52,36,-89,-105,47,-68,-48,-76,63,-52,-69,94,80,27,31,117,48,33,117,23,-113,-56,109,-113,36,63,63,49,37)\n18: 1\n19: 1\n20: false\n21: true\n22: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens(placeholder[Int](1))._1\n  if (coll2 == placeholder[Coll[Byte]](2)) {(\n    val box3 = OUTPUTS(INPUTS.indexOf(SELF, placeholder[Int](3)))\n    val coll4 = box3.R4[Coll[Long]].get\n    val coll5 = SELF.R4[Coll[Long]].get\n    val coll6 = box3.tokens\n    val tuple7 = coll6(placeholder[Int](4))\n    val coll8 = SELF.tokens\n    val tuple9 = coll8(placeholder[Int](5))\n    val tuple10 = coll6(placeholder[Int](6))\n    val tuple11 = coll8(placeholder[Int](7))\n    val l12 = tuple11._2\n    val coll13 = box1.R4[Coll[Long]].get\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          box3.value == SELF.value, box3.propositionBytes == SELF.propositionBytes, coll4(placeholder[Int](8)) == coll5(placeholder[Int](9)) + placeholder[\n            Long\n          ](10), box3.R5[Coll[Byte]].get == SELF.R5[Coll[Byte]].get, coll4(placeholder[Int](11)) == coll5(\n            placeholder[Int](12)\n          ), tuple7._1 == tuple9._1, tuple7._2 == tuple9._2, tuple10._1 == tuple11._1, tuple10._2 == l12 + coll13(placeholder[Int](13)) * l12 / coll13(\n            placeholder[Int](14)\n          )\n        )\n      )\n    )\n  )} else {(\n    val box3 = INPUTS(placeholder[Int](15))\n    if (box3.id == SELF.id) {(\n      val box4 = OUTPUTS(placeholder[Int](16))\n      sigmaProp((coll2 == placeholder[Coll[Byte]](17)) && if (box4.propositionBytes == SELF.propositionBytes) {(\n          val opt5 = box4.R5[Coll[Byte]]\n          if (opt5.isDefined) { (opt5.get == SELF.R5[Coll[Byte]].get) && (OUTPUTS(placeholder[Int](18)).tokens(placeholder[Int](19))._1 == box3.R5[Coll[Byte]].get) } else { placeholder[Boolean](20) }\n        )} else { placeholder[Boolean](21) })\n    )} else { sigmaProp(placeholder[Boolean](22)) }\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "1028de73d018f0c9a374b71555c5b8f1390994f2f41633e7b9d68f77735782ee",
          "index": 0,
          "amount": 1,
          "name": "ergopad Stake Token",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "d71693c49a84fbbecd4908c94813b46514b18b67a99952dc1e6e4791556de413",
          "index": 1,
          "amount": 12513673,
          "name": "ergopad",
          "decimals": 2,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1102a806d8d5cd9ce85f",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[404,1646076212588]"
        },
        "R5": {
          "serializedValue": "0e20708b05e0bca293b96fba2bf29ae7869201bddfbcde26cbf4c63e42d694905164",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "708b05e0bca293b96fba2bf29ae7869201bddfbcde26cbf4c63e42d694905164"
        }
      }
    },
    {
      "boxId": "63e8330cf7fd5c7dad658ae5b12b962a2713523bc2614f31fb14e2c7838f61cb",
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      "index": 2,
      "spendingProof": "011fba12d5abda41d44cd6c29bafa4777a4df8b77c0d13e9228b8b5b4c7eb61ac4293a5a7c736ee3e0bf6c2d7fdcc1e933b017002f67260b",
      "outputBlockId": "3aae4e8378ff90764aa6532e50566c390ec6a6586b54008acac4e2fd4a2b1b54",
      "outputTransactionId": "9c66783a6f20bd13cf60cc426f79f98ff902e3fb4b76fe9a28b8810f04200a0a",
      "outputIndex": 3,
      "outputGlobalIndex": 28094280,
      "outputCreatedAt": 977838,
      "outputSettledAt": 977840,
      "ergoTree": "0008cd03c3ce4fd9a252ec9e58a766481f7d09dae2c9c2c48f22b47d97c4af12347a2ffc",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(c3ce4f,97456a,...)))}",
      "address": "9hx3HoWVZ9ErUWmFAFi7XYTie6uUMWWwULuGVFdJFqNNf9CdRcB",
      "assets": [
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      "additionalRegisters": {}
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  ],
  "dataInputs": [],
  "outputs": [
    {
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      "transactionId": "7c098e105519cb15bef75d0b04aa0a1ea7dbae32096ec36bdb4c47eac77edbed",
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      "value": 1000000,
      "index": 0,
      "globalIndex": 28094356,
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      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 0\n4: 1\n5: Coll(-41,22,-109,-60,-102,-124,-5,-66,-51,73,8,-55,72,19,-76,101,20,-79,-117,103,-87,-103,82,-36,30,110,71,-111,85,109,-28,19)\n6: 0\n7: 0\n8: 4\n9: 4\n10: 2\n11: 1\n12: 1\n13: 2\n14: 0\n15: 0\n16: 0\n17: 1\n18: 2\n19: 2\n20: 1\n21: 3\n22: 3\n23: 1\n24: Coll(37,-73,72,107,26,120,100,122,-41,-43,10,40,126,94,-107,-117,78,69,42,75,-56,105,56,-55,66,24,-41,6,-68,55,127,-16)\n25: 0\n26: 1\n27: 1800000\n28: 1\n29: 1000\n30: 1\n31: 1\n32: 1\n33: 0\n34: Coll(13,1,-14,-16,-77,37,75,74,23,49,-31,-74,26,-41,118,65,-2,84,-34,43,-42,-115,28,111,-63,-82,78,126,-99,-33,-78,18)\n35: 3\n36: 2\n37: 1\n38: 3\n39: 0\n40: Coll(5,73,-22,51,116,-93,107,122,34,-88,3,118,106,-9,50,-26,23,-104,70,60,51,50,-59,-10,-40,108,-118,-71,25,94,-19,89)\n41: 1\n42: 1\n43: 2\n44: 0\n45: 1\n46: 1\n47: 2\n48: 2\n49: 3\n50: 0\n51: 0\n52: 3\n53: 0\n54: 0\n55: 1\n56: 0\n57: 0\n58: -999999999999\n59: 1\n60: 604800000\n61: 8\n62: 0\n63: 6\n64: 5\n65: 100\n66: 4\n67: 125\n68: 1000\n69: 2\n70: 20\n71: 100\n72: 25\n73: 100\n74: 2\n75: 0\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 1\n82: 2\n83: 2\n84: 1\n85: 0\n86: 3\n87: 3\n88: 1\n89: 0\n90: 0\n91: 2\n92: 0\n93: 1\n94: 1000\n95: 0\n96: 1\n97: true\n98: false",
      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val tuple3 = coll2(placeholder[Int](1))\n  val coll4 = tuple3._1\n  val coll5 = SELF.tokens\n  val tuple6 = coll5(placeholder[Int](2))\n  val coll7 = tuple6._1\n  val bool8 = coll4 == coll7\n  val box9 = OUTPUTS(placeholder[Int](3))\n  val coll10 = box9.R4[Coll[Long]].get\n  val coll11 = SELF.R4[Coll[Long]].get\n  val l12 = tuple6._2\n  val coll13 = box9.tokens\n  val tuple14 = coll13(placeholder[Int](4))\n  val l15 = tuple14._2\n  val l16 = CONTEXT.preHeader.timestamp\n  val l17 = tuple3._2\n  val coll18 = placeholder[Coll[Byte]](5)\n  val tuple19 = coll13(placeholder[Int](6))\n  val tuple20 = coll5(placeholder[Int](7))\n  val l21 = coll11(placeholder[Int](8))\n  val bool22 = allOf(\n    Coll[Boolean](\n      box9.propositionBytes == SELF.propositionBytes, box9.value == SELF.value, tuple19._1 == tuple20._1, tuple19._2 == tuple20._2, tuple14._1 == coll7, coll10(\n        placeholder[Int](9)\n      ) == l21, coll13.size == placeholder[Int](10)\n    )\n  )\n  if (bool8) {(\n    val tuple23 = coll2(placeholder[Int](11))\n    val l24 = tuple23._2\n    val l25 = coll11(placeholder[Int](12))\n    val coll26 = box1.R4[Coll[Long]].get\n    val coll27 = box1.R5[Coll[Byte]].get\n    val box28 = OUTPUTS(placeholder[Int](13))\n    val tuple29 = box28.tokens(placeholder[Int](14))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          bool22, coll10(placeholder[Int](15)) == coll11(placeholder[Int](16)) + l24, coll10(placeholder[Int](17)) == l25, coll10(\n            placeholder[Int](18)\n          ) == coll11(placeholder[Int](19)) + placeholder[Long](20), coll10(placeholder[Int](21)) == coll11(placeholder[Int](22)), l15 == l12 - placeholder[\n            Long\n          ](23), blake2b256(box1.propositionBytes) == placeholder[Coll[Byte]](24), coll26(placeholder[Int](25)) == l25, coll26(\n            placeholder[Int](26)\n          ) >= l16 - placeholder[Long](27), coll27 == SELF.id, bool8, l17 == placeholder[Long](28), tuple23._1 == coll18, l24 >= placeholder[Long](\n            29\n          ), box28.propositionBytes == INPUTS(placeholder[Int](30)).propositionBytes, tuple29._1 == coll27, tuple29._2 == placeholder[Long](31)\n        )\n      )\n    )\n  )} else {(\n    val box23 = INPUTS(placeholder[Int](32))\n    val coll24 = box23.tokens\n    val tuple25 = coll24(placeholder[Int](33))\n    val coll26 = tuple25._1\n    if ((coll26 == placeholder[Coll[Byte]](34)) && (INPUTS.size >= placeholder[Int](35))) {(\n      val box27 = INPUTS(placeholder[Int](36))\n      val coll28 = box27.R4[Coll[Long]].get\n      val l29 = coll11(placeholder[Int](37))\n      val l30 = coll10(placeholder[Int](38))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            bool22, box27.tokens(placeholder[Int](39))._1 == placeholder[Coll[Byte]](40), coll28(placeholder[Int](41)) == l29 - placeholder[Long](42), coll28(\n              placeholder[Int](43)\n            ) == placeholder[Long](44), coll10(placeholder[Int](45)) == l29 + placeholder[Long](46), coll10(placeholder[Int](47)) == coll11(\n              placeholder[Int](48)\n            ), l30 == coll11(placeholder[Int](49)) + l21, l30 < l16, l15 == l12\n          )\n        )\n      )\n    )} else {(\n      val l27 = coll11(placeholder[Int](50))\n      val l28 = coll10(placeholder[Int](51))\n      if ((l27 > l28) && (INPUTS.size >= placeholder[Int](52))) {(\n        val func29 = {(coll29: Coll[Box]) => coll29.fold(placeholder[Long](53), {(tuple31: (Long, Box)) =>\n              val coll33 = tuple31._2.tokens\n              val l34 = tuple31._1\n              if (coll33.size == placeholder[Int](54)) { l34 } else {(\n                val coll35 = coll33.filter({(tuple35: (Coll[Byte], Long)) => tuple35._1 == coll18 })\n                val i36 = coll35.size\n                if (i36 == placeholder[Int](55)) { l34 + coll35(placeholder[Int](56))._2 } else { if (i36 == placeholder[Int](57)) { l34 } else { placeholder[Long](58) } }\n              )}\n            }) }\n        val l30 = func29(INPUTS)\n        val l31 = func29(OUTPUTS)\n        val coll32 = box23.R4[Coll[Long]].get\n        val l33 = coll32(placeholder[Int](59))\n        val l34 = l16 - l33 / placeholder[Int](60).toLong\n        val l35 = l27 - l28\n        val l36 = if (l34 >= placeholder[Long](61)) { placeholder[Long](62) } else {\n          if (l34 >= placeholder[Long](63)) { l35 * placeholder[Long](64) / placeholder[Long](65) } else {\n            if (l34 >= placeholder[Long](66)) { l35 * placeholder[Long](67) / placeholder[Long](68) } else {\n              if (l34 >= placeholder[Long](69)) { l35 * placeholder[Long](70) / placeholder[Long](71) } else {\n                l35 * placeholder[Long](72) / placeholder[Long](73)\n              }\n            }\n          }\n        }\n        val box37 = INPUTS(placeholder[Int](74))\n        val l38 = coll32(placeholder[Int](75))\n        val l39 = coll11(placeholder[Int](76))\n        val tuple40 = coll24(placeholder[Int](77))\n        val l41 = tuple40._2 - l35\n        val bool42 = l41 == placeholder[Long](78)\n        val coll43 = tuple40._1\n        sigmaProp(\n          allOf(\n            Coll[Boolean](\n              l30 > placeholder[Long](79), l31 > placeholder[Long](80), l30 - l31 == l36, bool22, box37.tokens.exists(\n                {(tuple44: (Coll[Byte], Long)) => tuple44._1 == box23.R5[Coll[Byte]].get }\n              ), l38 == l39, l28 == l27 - l35, coll10(placeholder[Int](81)) == l39, coll10(placeholder[Int](82)) == coll11(placeholder[Int](83)) - if (bool42) {\n                placeholder[Long](84)\n              } else { placeholder[Long](85) }, coll10(placeholder[Int](86)) == coll11(placeholder[Int](87)), l15 == l12 + if (bool42) {\n                placeholder[Long](88)\n              } else { placeholder[Long](89) }, box1.propositionBytes == box37.propositionBytes, coll4 == coll43, l17 == l35 - l36, if (l41 > placeholder[Long](\n                90\n              )) {(\n                val box44 = OUTPUTS(placeholder[Int](91))\n                val coll45 = box44.tokens\n                val tuple46 = coll45(placeholder[Int](92))\n                val tuple47 = coll45(placeholder[Int](93))\n                val coll48 = box44.R4[Coll[Long]].get\n                allOf(\n                  Coll[Boolean](\n                    box44.value == box23.value, tuple46._1 == coll26, tuple46._2 == tuple25._2, tuple47._1 == coll43, tuple47._2 == l41, l41 >= placeholder[\n                      Long\n                    ](94), coll48(placeholder[Int](95)) == l38, coll48(placeholder[Int](96)) == l33\n                  )\n                )\n              )} else { placeholder[Boolean](97) }\n            )\n          )\n        )\n      )} else { sigmaProp(placeholder[Boolean](98)) }\n    )}\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "05cde13424a7972fbcd0b43fccbb5e501b1f75302175178fc86d8f243f3f3125",
          "index": 0,
          "amount": 1,
          "name": "ergopad Stake State",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "1028de73d018f0c9a374b71555c5b8f1390994f2f41633e7b9d68f77735782ee",
          "index": 1,
          "amount": 999996539,
          "name": "ergopad Stake Token",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1105a6acf4cf8601a8068a36c886f6d0eb6180f0b252",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[18068966163,404,3461,1680893460900,86400000]"
        }
      },
      "spentTransactionId": "be8e70360abed5ae9a1bfa4d56b56963dea63404f4f06f00f5de088c24c13b87",
      "mainChain": true
    },
    {
      "boxId": "31cb28fbbfc62e70f6c739614637d872ff50640ede3a6c24291d72b2ad88997d",
      "transactionId": "7c098e105519cb15bef75d0b04aa0a1ea7dbae32096ec36bdb4c47eac77edbed",
      "blockId": "a9c15d7076f8fcb08fd756f485bff5e1e3edb28064f063f3931033746aa2e4b9",
      "value": 10000000,
      "index": 1,
      "globalIndex": 28094357,
      "creationHeight": 977842,
      "settlementHeight": 977844,
      "ergoTree": "0008cd03c3ce4fd9a252ec9e58a766481f7d09dae2c9c2c48f22b47d97c4af12347a2ffc",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(c3ce4f,97456a,...)))}",
      "address": "9hx3HoWVZ9ErUWmFAFi7XYTie6uUMWWwULuGVFdJFqNNf9CdRcB",
      "assets": [
        {
          "tokenId": "d71693c49a84fbbecd4908c94813b46514b18b67a99952dc1e6e4791556de413",
          "index": 0,
          "amount": 12513673,
          "name": "ergopad",
          "decimals": 2,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "e04437b1862ba07a91101c323fe6dcadc0b089e2a929d9325366db9e750600b4",
      "mainChain": true
    },
    {
      "boxId": "0d3c8bbe6b61eae79e5f3845bd33363156219b53bc7f2da9fa15cbaab66fa25c",
      "transactionId": "7c098e105519cb15bef75d0b04aa0a1ea7dbae32096ec36bdb4c47eac77edbed",
      "blockId": "a9c15d7076f8fcb08fd756f485bff5e1e3edb28064f063f3931033746aa2e4b9",
      "value": 1000000,
      "index": 2,
      "globalIndex": 28094358,
      "creationHeight": 977842,
      "settlementHeight": 977844,
      "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)}",
      "address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "a04f32a7c658a9e26c6cea7654e3fa54478770e255fc30a33499c4f3cf04b2a6",
      "mainChain": true
    },
    {
      "boxId": "795905c27aa2fbbd2496ae55bfce4bdb5d0b525439a4d87ba3a62d7391af1065",
      "transactionId": "7c098e105519cb15bef75d0b04aa0a1ea7dbae32096ec36bdb4c47eac77edbed",
      "blockId": "a9c15d7076f8fcb08fd756f485bff5e1e3edb28064f063f3931033746aa2e4b9",
      "value": 29826947220,
      "index": 3,
      "globalIndex": 28094359,
      "creationHeight": 977842,
      "settlementHeight": 977844,
      "ergoTree": "0008cd03c3ce4fd9a252ec9e58a766481f7d09dae2c9c2c48f22b47d97c4af12347a2ffc",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(c3ce4f,97456a,...)))}",
      "address": "9hx3HoWVZ9ErUWmFAFi7XYTie6uUMWWwULuGVFdJFqNNf9CdRcB",
      "assets": [
        {
          "tokenId": "372df84129b15baa62d5ef4fe6e96069eb044482bf09b89e569b533181bbd283",
          "index": 0,
          "amount": 1,
          "name": "Ergnome #188 Pedro, the Ripped Pirate Pellican",
          "decimals": 0,
          "type": "EIP-004"
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