{
  "boxId": "f1524b455e77a7c820e875c2dba6d33c31d36841483d431c52f1060af95e6c94",
  "transactionId": "1caed366f253153ddcad36bcf89ee4b5a8d3e39d150affa9f46850ff9eea80fe",
  "blockId": "49d90a94e45426155506e2eab070bbb0c801d15da36613f9100829c09eec7574",
  "value": 2000000,
  "index": 0,
  "globalIndex": 1132766,
  "creationHeight": 1168270,
  "settlementHeight": 1168272,
  "ergoTree": "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",
  "ergoTreeConstants": "0: 0\n1: 0\n2: Coll(44,-104,-93,-28,46,63,122,-102,19,47,-39,55,87,15,-92,-108,31,-47,-78,104,30,-76,95,115,-69,49,113,57,-102,-59,-27,88)\n3: Coll(85,-65,-103,59,67,118,-70,19,34,100,-48,-124,-16,111,-32,51,50,26,-76,60,104,-37,20,53,-96,-25,-32,-65,119,-35,-73,53)\n4: true\n5: 1\n6: 1\n7: 2\n8: 2\n9: 0\n10: -1\n11: 1\n12: 2\n13: 0\n14: Coll(113,53,-12,-30,-94,-37,-74,95,-111,108,114,30,74,-118,89,-96,-120,-108,-72,101,12,74,35,34,60,-50,19,-79,-80,-112,-77,68)\n15: -1\n16: 1\n17: 3\n18: 5\n19: 1\n20: 0\n21: 0\n22: 0\n23: 4\n24: 0\n25: 0\n26: true\n27: 1\n28: 1\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 1\n35: 0\n36: 0\n37: 1\n38: 1\n39: 0\n40: 0\n41: 0\n42: 0\n43: 3",
  "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 = placeholder[Coll[Byte]](2)\n  if (coll4 == placeholder[Coll[Byte]](3)) { sigmaProp(placeholder[Boolean](4)) } else {(\n    val coll6 = SELF.tokens\n    val tuple7 = coll6(placeholder[Int](5))\n    val l8 = tuple7._2\n    val tuple9 = coll2(placeholder[Int](6))\n    val l10 = tuple9._2\n    val tuple11 = coll2(placeholder[Int](7))\n    val l12 = tuple11._2\n    val tuple13 = coll6(placeholder[Int](8))\n    val l14 = tuple13._2\n    val coll15 = tuple7._1\n    val coll16 = SELF.R6[Coll[Long]].get\n    val tuple17 = coll6(placeholder[Int](9))\n    val coll18 = tuple13._1\n    val coll19 = box1.R4[Coll[Coll[Byte]]].get\n    val coll20 = box1.R5[Coll[Long]].get\n    val i21 = coll20.size\n    val bool22 = allOf(\n      Coll[Boolean](\n        box1.propositionBytes == SELF.propositionBytes, box1.R6[\n          Coll[Long]\n        ].get == coll16, coll4 == tuple17._1, tuple3._2 == tuple17._2, tuple9._1 == coll15, tuple11._1 == coll18, coll19.size == i21\n      )\n    )\n    val coll23 = SELF.R5[Coll[Long]].get\n    val i24 = coll23.size\n    if (l8 > l10) {(\n      val i25 = box1.R7[Int].getOrElse(placeholder[Int](10))\n      val l26 = l8 - l10\n      val box27 = OUTPUTS(placeholder[Int](11))\n      val box28 = OUTPUTS(placeholder[Int](12))\n      val tuple29 = box27.tokens(placeholder[Int](13))\n      val bool30 = allOf(\n        Coll[Boolean](bool22, l26 == l12 - l14, tuple29._2 == l26, tuple29._1 == coll15, blake2b256(box27.propositionBytes) == placeholder[Coll[Byte]](14))\n      )\n      if (i25 == placeholder[Int](15)) {(\n        val i31 = i21 - placeholder[Int](16)\n        val coll32 = SELF.id\n        val box33 = OUTPUTS(placeholder[Int](17))\n        val l34 = coll16(placeholder[Int](18))\n        sigmaProp(\n          allOf(\n            Coll[Boolean](\n              bool30, i21 == i24 + placeholder[Int](19), coll19.slice(placeholder[Int](20), i31) == SELF.R4[Coll[Coll[Byte]]].get, coll19(\n                i31\n              ) == coll32, coll20.slice(placeholder[Int](21), i31) == coll23, coll20(i31) == l26, box27.R4[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n                coll32\n              ), box28.tokens(placeholder[Int](22))._1 == coll32, blake2b256(box33.propositionBytes) == coll5, box33.R4[\n                Coll[Byte]\n              ].get == coll32, box33.value >= coll16(placeholder[Int](23)), if (l34 > placeholder[Long](24)) {(\n                val tuple35 = box33.tokens(placeholder[Int](25))\n                allOf(Coll[Boolean](tuple35._1 == coll18, tuple35._2 >= l34))\n              )} else { placeholder[Boolean](26) }\n            )\n          )\n        )\n      )} else {(\n        val coll31 = SELF.R4[Coll[Coll[Byte]]].get\n        val coll32 = coll31(i25)\n        val i33 = i25 + placeholder[Int](27)\n        sigmaProp(\n          allOf(\n            Coll[Boolean](\n              bool30, coll32 == INPUTS(placeholder[Int](28)).tokens(placeholder[Int](29))._1, coll19 == coll31, coll20(i25) == coll23(i25) + l26, coll20.slice(\n                placeholder[Int](30), i25\n              ) == coll23.slice(placeholder[Int](31), i25), coll20.slice(i33, i21) == coll23.slice(i33, i21), box27.R4[Coll[Coll[Byte]]].get == Coll[\n                Coll[Byte]\n              ](coll32), box28.tokens(placeholder[Int](32))._1 == coll32\n            )\n          )\n        )\n      )}\n    )} else {(\n      val coll25 = SELF.R4[Coll[Coll[Byte]]].get\n      val i26 = box1.R7[Int].get\n      val l27 = l10 - l8\n      val l28 = coll23(i26)\n      sigmaProp(\n        allOf(Coll[Boolean](bool22, Coll[Coll[Byte]](coll25(i26)) == INPUTS(placeholder[Int](33)).R4[Coll[Coll[Byte]]].get, l27 == l14 - l12, if (l28 > l27) {(\n              val i29 = i26 + placeholder[Int](34)\n              allOf(Coll[Boolean](l28 == coll20(i26) + l27, coll25 == coll19, coll23.slice(placeholder[Int](35), i26) == coll20.slice(placeholder[Int](36), i26), coll23.slice(i29, i24) == coll20.slice(i29, i24)))\n            )} else {(\n              val i29 = i26 + placeholder[Int](37)\n              allOf(Coll[Boolean](i21 == i24 - placeholder[Int](38), l28 == l27, coll25.slice(placeholder[Int](39), i26) == coll19.slice(placeholder[Int](40), i26), coll25.slice(i29, i24) == coll19.slice(i26, i21), coll23.slice(placeholder[Int](41), i26) == coll20.slice(placeholder[Int](42), i26), coll23.slice(i29, i24) == coll20.slice(i26, i21), blake2b256(INPUTS(placeholder[Int](43)).propositionBytes) == coll5))\n            )}))\n      )\n    )}\n  )}\n}",
  "address": "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",
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    {
      "tokenId": "eceee4b72d8572c032789927a1847557292fb80b78fb58d6214754d2d474272d",
      "index": 0,
      "amount": 1,
      "name": "rspv1RWTNFT",
      "decimals": 0,
      "type": "EIP-004"
    },
    {
      "tokenId": "bee1398b0a7acc0a4a0bc8619ef473a462f4c23208072f2aaeddfef67d30166a",
      "index": 1,
      "amount": 997282507315,
      "name": "rspv1CardanoRWT",
      "decimals": 3,
      "type": "EIP-004"
    },
    {
      "tokenId": "8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b",
      "index": 2,
      "amount": 2717492686,
      "name": "RSN",
      "decimals": 3,
      "type": "EIP-004"
    }
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  "additionalRegisters": {
    "R4": {
      "serializedValue": "1a4d0763617264616e6f20c6ccbad58cdcf2382e8154724b8991c54d498831188e3d47e628afbaa9897db520745d0ddfb294d7dc9812b3594d4d03ed1cc0ad824f7c73b91eb635c731c75478203d83a4ab97bbe3e9278af955882b1171bc201faa87b066e744fad61da580170c20aced39348632357775564aabf3d78d6248b05c70259f7e9133a0c41af26d0eeb209c29664c8f13f89554c6392e7ff2ffb0e8c503ef6b5b8dba4f2e52f61b99a154204acca9325ddbad467d9768116258b52968a0b9974c2549109f94fad7947b712f20270894e35f27daee400150c9c7996e64f615828c976a5906f9b1998a749070792052b8e50ab08a3d13701fcfec128ed2acff11dfb17c8c169ba6c87b5b016d5c43203944ab8c5682b2871fb73e57958f9c720826662fa86848353f46ac4ffcd31deb20d60405821beec8f85d8ca5916c46f4f05a0ae48a03ec9830b0239c0cb3617bfb20952bf9e7cfd3190be16d40a24e60441960f1b1b826ba7589516db0d3f895716120ae3a1c919c4b5e3b831a62396441882b7cecc440b9666a273dbd6abd0751a15220d143e889d67a6cffe25c9e75919525660473c5946cb08429fb5c2b938ffcbca82087d76b69ef05f09b62ea12906c38c9106207ed86ff49e0a3ef4053faa1ce61d420e42265bf88468ac9d96bc1e01790f11df8b6c3be3a5655df7d6f8197ef07079420b40729cd9e076dfc4a2b2dcd822560025351085fe2b79a18abb1373b89a780e92086e2e47f57623dc5eba650f130e0953baa6784ace4ac37c37d791639706bb14f2003310f1404169ec32948f0af18b057f54371f9982514ecc44043c137fa58c5332064579f3015feb870475d0d057fc431f8b037a19091e12cad0d2f0dd8229cffec200e748945c4de1860fe90ccf65e8883e35525fe2b7a8108c3d25c7d4cf7f9275620e0b226e1f2dc8e442c4792cfbfbc9f0474c3ccdb3d7e5ade69721acfac9aaabc20b1e61e565db9ed3d89b28c3c72a959aa8e6c1775e540e46e5bfdd6ed08e24ce220feef7062ca6d96af52a840af10890ab50620d925075dfb19397709bc4fb379c420f02db07c654b443eea4b8773fd47f786b95196c4afc1fb46562606945ba490e9205818eb5d911ecd2b9f09a680e2b84bcaa281f624fb67c3e9b97d7cb01fc71da42051dc02e54e6e3eb9c9736b40ec59c19681e0beda61c76058a0fb41978bff999c209e06c53dac95224036d941d176cc9893e7f7c0e8376ea1555d6a42f0bbe8c02c203effc426ba46fec9be13992cc9c38f205944c8d5bdf90f0c99a5b5850a61bc702096da61372142ca01e79384414f682753315c2270f2585f8af697d05f1e792e11202c1f4ecd011968d7faacec7be81ae207ef05b036c0172539c5f3dba43d10b05e20778c65f5171c5690990eb7dd08f210509c39d84a6aabc50afa8988a746e520ba20fd0595d39a98f632dcb5db279ce545bab3e24eea1dce02e507739aeb7eb767eb208606f31f2d44ae4ed590bc9de4ea5f0692c842c102da527d1d123b8fcd024c0320243fdb81eeeebf81c67554062ba3b9cff03ba22e3ad85ab75c2930a948fa10bd20a95e27d5890c5af17a62fed098fbd41a372fa46db9e0f7521dee42bc9cb1393620441f3a2b69b0dc7fd8a1b5b90dac5bea494319007155577880733b9660f55ac120d2d5b1d12dc6f06406dd6ed6a196447aa9414fca80bfb89009b52c190ff96e2220e5b8a00cce25bcece9f11f5c6354f4cb6172bd009556069c1f19cfa0c73dae8c20520399bc0486111aabbae6d3163aafd0d8aabed990db0255b09ae911cafb975a207311710e4017f7deed3e33ffcd9c1ded5279a0ba8256f52133c2c8648a4cddf1208ca71f357841d289246dcde321a162d76c01649b235a5f902617de6b027e371220bf34ef36c34366bfe9076573c94af5434d416318ebaba8a0c623b28cbd921c6820656708fdd4aefe28b7e87841d4a5f20334d28114a384aa1acc065cda060ba72620f2fb51c7bacdd5e08a2d905b1238adf0a669e7c214570880b0f0bf4b0672acba2046d6f4f080d5d185773a001d6ff796a3883b39725b777db9ecacedb626ecc445207b61f2e442e19f328e38b404f10ad1f30e02bd4e2cebaf167967008468dd8407200fe391e2d5774484c6589aa375187a3b5ebe436f84b1151f6df9bf5e9adea76a2084598de02112b1879284c203f98ecae2cbe90b6afdfc37c8241e39d6b8e2a91d20903329af618fda088fcd150398dc1c094e1c515ad0a3cb5edcc338420ee8fab220f2ae66fd7544496701d7f29f66b614bc93406aa25619ce253a91c1c40ccde95820f8985009d52e6d8d3ce951cb8ba79d74d5ef6c19753c63974bd61543f5e3923c20a059ddc0320c39de18721444a74be4acf66f6fddbfd46f15d1113f2e18264dba209253a888fb7fb1f1e7fb16940aac8b793833d2d19ab2d982543f24a3b15a3d51201db48c3ff54cceea1982f95c0dd3f4683da74566d59cc12186c8185c3b1f1fa4208e4e3b445ed86917bb4b72bf6b6a81b592169adae87e870a93340c1c29b92d3a20e5f4afae0ce544d3e1d705724bfa042d3b60db3c449ac84ce7d3be7a291fd90f20e66ddb385bafbb373bf4b9735b96b2c3e1ba3e654a8d1b91ccb4d1bc8edb6e1a205ce706d382cf0fb737c726b0970015bcf9e4ae76aadf12b4068ac3e5b6db86842041788509b744735a550b56a2c9edd1d90a79225aa054742b6355f8291c1ac1c720e7707b4ef4315172a6678d31aa6b91a118537a998972cc36739cc478a72421d920ac91a8dc441f665f6f592754f9776d3716a300a51b8ef8cc07b5ebf3249b87aa20477df4283fa7278e82de362e9e3067fef28a7959eb79291bf905077feb06e7cc20c69d97f4fdacf77b6719e364a654d2f5c9ea2a26ede80c81880fb679bc154cc220edb54bd783ba8df4e75c707bcb24192129ede7adad60b1d53c3307bb616411062068cd1848a9933cc4eb36d09b6ba39812e8daaa2b20c196f1efa10b30b83a9ad3202b30e5582145f9bcedfa8a2aa86298ac8a5231ad8945254dfd615b56c93b7af52053a12d63d8fd389a86a54575838cbc37af4a54813b35d7d036d653eca9a53323205e65be4e2e83b87364012b7747f7d0c06f60585cb3193a0de43807a6c4130fe9209bd34f9eb406a0142593f3606893ac671c37be0bdeb2d3f836f24854b8159608209db24719e5c22c9c341c6b270284fe39927cf9045df2b70eae655f8741ed6766202a7f8c59033f9773ef1593b126b71332a92f310fc900dd6b59b70ec963602be9209008014c851d04af437550b9de80adc5a573fb3751c8c119a19626893ac3d95120fa93303bcf6cd09a90a81dc552db699424075ee615c15f3e058477ff9833f3e8207eb47dc621d93d5c6d6cfdb9f5df96592a29b99eb6a04067b6c1144b47c31fdb20d49434259fd765089b9095e9ea00d9746c9837e488842c9081441da4dcccb951207871f0a716ad6f258cee6029c10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