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Transaction

7/30/2023 12:35:56 PM
ID: 10434ecbd9...c873
Inputs (11)
#0
d52d348fc802...9b60
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
6de5f89c2930...d25c
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#1
2d69c1a95389...924f
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
1652e41ed2f5...b0cb
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#2
eeea5ab9b3e8...b0fd
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
2c4bdae0d930...8667
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#3
c442e10bf801...3502
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
4f89a4d30259...3adf
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#4
55ed85be4fa3...dad7
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
640eadff23a3...299d
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#5
194ea48a5b15...751e
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
8c03cd1d1ee7...d724
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#6
045272057d62...7381
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
9bca9cf58998...5d30
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#7
671e67cd105f...bdd5
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
bf10395093f4...116c
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#8
8b0559b0312c...7e6a
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
c570f52950c1...c5f6
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#9
01dd8299ac33...1651
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
c9f5ab582f72...8c64
Settlement height:
1,058,178
Value:
0.0011 ERG
Tokens:
Loading assets...
#10
bfaad3557c26...ce7e
Spent
Address:
9gVkEXyFWKGk...LWRu
Output transaction:
bf10395093f4...116c
Settlement height:
1,058,178
Value:
1.99 ERG
Tokens:
Loading assets...
Outputs (3)
#0
4ac971c3faec...98ea
Spent
Address:
BRNzuPCshtnB...Hyvp
Spent in transaction:
132c642fb871...073a
Settlement height:
1,058,190
Value:
0.011 ERG
Tokens:
Loading assets...
#1
cdc06c2f8c7b...128b
Spent
Address:
9gVkEXyFWKGk...LWRu
Spent in transaction:
215bc219ea07...c21f
Settlement height:
1,058,190
Value:
1.99 ERG
Tokens:
Loading assets...
#2
7358105e7ec3...6692
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
760c4e747dd5...d0b4
Settlement height:
1,058,190
Value:
0.0011 ERG
Transaction Details
Status: Confirmed
Size: 1.74 KB
Received time: 7/30/2023 12:35:56 PM
Included in blocks: 1,058,190
Confirmations: 718,754
Total coins transferred: 2 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000618 ERG
Raw Transaction Data
{
  "id": "10434ecbd9595f9955947eb70920d098e7a4d520e8577f70fc4a59901eb7c873",
  "blockId": "99b7828ca5d99cafbb88c9de991a79dc46d9955a5d97ca2b70fee1ebbf25c5bb",
  "inclusionHeight": 1058190,
  "timestamp": 1690720556608,
  "index": 8,
  "globalIndex": 5595925,
  "numConfirmations": 718754,
  "inputs": [
    {
      "boxId": "d52d348fc80219dac4a74816e53c0bae3d0e951d788101dbb3883154e9c29b60",
      "value": 1100000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "1113fc5a3c0ec6a706364df3b0b49cc1ddd6c39a6eecc66027ea79b826e89712",
      "outputTransactionId": "6de5f89c293046adb32a135841a0a2f7f1104e724f507facae2f90087fead25c",
      "outputIndex": 1,
      "outputGlobalIndex": 31387024,
      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "3825b2b4acaaaba626440113153246c65ddb2e9df406c4a56418b5842c9f839a",
          "index": 0,
          "amount": 10000,
          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1a012090829fb915dba5c834d14b0e1e1387f6c2e4760965b8cd338892e4ad13baab3d",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[90829fb915dba5c834d14b0e1e1387f6c2e4760965b8cd338892e4ad13baab3d]"
        },
        "R5": {
          "serializedValue": "1a0120d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de]"
        },
        "R6": {
          "serializedValue": "0e201a19b4e882c1e98e16b0b2351a049fbc333ab031f99a0b3546381e1e2d56b100",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "1a19b4e882c1e98e16b0b2351a049fbc333ab031f99a0b3546381e1e2d56b100"
        },
        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
      }
    },
    {
      "boxId": "2d69c1a953895bb5f71b38d329a93ba30793935f6aef05c9f25149754dda924f",
      "value": 1100000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "1113fc5a3c0ec6a706364df3b0b49cc1ddd6c39a6eecc66027ea79b826e89712",
      "outputTransactionId": "1652e41ed2f51e58f37607ed91488083e34176c34caddb530544c1685a50b0cb",
      "outputIndex": 1,
      "outputGlobalIndex": 31387028,
      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
      "address": "4YCK14N7W9YbyjptY8DSQeeQamjxynHZsRaxXZN7TTHDJtMR5qtkMQzzkkNu9SXkYjVYpgcRuHXg7MiEY5PUYwyhPSaKGhPWrCvYjV9oTuwWRrSdBgVh9qsw5jAhS38ft9b8daJqTHsrqMmguCDuqu6wQ7p8nd6ZrCXkih9QL6HtdoFkYATQQ4NnVaZepHV6EQ7jF5G5SiHnMzXr8ea3NqDkybhtMxsA1p8TXrt2FyDvXUeS5hoApNHvL56bxTypBnw2bi6PHnFyVTWwbZn91nqt3vQxRzVAu4kpxfmkMvnwfcDQPMKvsrVAavJKPc17DgRdumezfxU1ktQBj5mTwghdbC3AsCEQyMHG3SsLM8Gi68rr9GWs4C3msumYQfKMhcyNMAcibkW7VfGgMFBCJ1QXmJAm4P9x2ZP8WELKU4eYHXD3CbDMBwYBTkQFGm5pWsQdFRw1fa7hs4cZxQYp4vghFjVtHV5r9TXy8VhvCPKw9jv4TLdqPEG3GZ4paU9vqetHFPuHkXoK55Jwa3LW78mjqzotNuBK4BVGcwJiqp3XUpfuwLX9TVqeaTh3oogRPZLvNGV4uS8HoqCge7rqGDFSMXZAViQyL9A9tSiUVzyvL28ugGWDxpsUoe3bhGRipTEMcAkdFqGCvrhpxCow7VJS5sXj5y4CbsBMJ3bV1opihoqUmeYoZi5FZJPka4vA29dDS2qftsvWngEXEmWaCbxNfUiEGKY6shJHGczY3kf7qWhU9tYgWeA2DEjKzCB2rd2uGDSfk73RBbMZk1R6g59rkucuTTz1YJCLmSxuogBjzuZVYG8C4Lx4VR3ysSHFDikBmEaYoV6Kpt8aNdrEgb75Bfs6YLqVKeQX3KPPm4nFmY9i1GxpzJCGxPyR8Rni9ivZSt11S7orzWZFAKSX3CEzCHKrCci6NmoWo5JiTZNpN3fCDd",
      "assets": [
        {
          "tokenId": "3825b2b4acaaaba626440113153246c65ddb2e9df406c4a56418b5842c9f839a",
          "index": 0,
          "amount": 10000,
          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1a0120e61a83c5bca59e98c21d925faff5dfc079aa438f21df08702e4c4bf2bada02dc",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[e61a83c5bca59e98c21d925faff5dfc079aa438f21df08702e4c4bf2bada02dc]"
        },
        "R5": {
          "serializedValue": "1a0120d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de]"
        },
        "R6": {
          "serializedValue": "0e200309a97a2f25862c5836779bc289f67da8bcb25a25bb01dc1d70caafc2ac76dc",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0309a97a2f25862c5836779bc289f67da8bcb25a25bb01dc1d70caafc2ac76dc"
        },
        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
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    {
      "boxId": "eeea5ab9b3e80a65affd758de905b3a63b9dcd219a6f5dd9ccc03ffc6b0bb0fd",
      "value": 1100000,
      "index": 2,
      "spendingProof": null,
      "outputBlockId": "1113fc5a3c0ec6a706364df3b0b49cc1ddd6c39a6eecc66027ea79b826e89712",
      "outputTransactionId": "2c4bdae0d930dff3976c2b02bf292ae45111652219a24caafcff93c5ac188667",
      "outputIndex": 1,
      "outputGlobalIndex": 31387033,
      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "101c04000e20420b2e9fb2bcddedff650be63b1acbc26bc0bddd255b00325087aa5595a89a3a040002000402040004000400040004000400040604040402050205c801040004000400050004020400040004000400040204000400d80ad601b2a4730000d6027301d60393cbc272017202d604e4c6a7041ad6059572037201b2a5730200d606e4c67205041ad607e4c67205051ad608b072078301027303d901083c0e0eb38c7208018c720802d609b472087304b17208d60ab2a5730500957203d803d60bb2b5a5d9010b63d801d60dc6720b041aede6720d93e4720d7204730600d60cb2db6308720b730700d60db2db6308a7730800d19683050193cbc2720be4c6a7070e938c720c018c720d01938c720c028c720d02efae7206d9010e0e93720483010e720e93cbb37209b27204730900e4c6a7060ed801d60bcbc2720a9593720b7202d80ad60cb5a4d9010c6393c2a7c2720cd60db1720cd60e7e720d05d60fb2db6501fe730a00d610e4c6720f0611d611b27210730b00d6129ab27210730c009d9cb27210730d00997eb1e4c6720f041a05730e730fd613b2db6308a7731000d614b27210731100d615b2db63087205731200d196830b0192c1720ab0ad720cd9011663c172167313d90116599a8c7216018c72160293b1b5720cd901166393e4c67216041a72047314ae7206d901160e9383010e7216720493e4c67205060ee4c6a7070e93b17206720d93cbb37209b27204731500e4c6a7060e93e4c6a7051a83010ecbb2720773160091720e958f7211721272117212938c7213027214938c7215029c7214720e938c7215018c721301d802d60cb2db6308720a731700d60db2db6308a7731800d19683060193c5a7c57201938c720c018c720d01938c720c028c720d0293e4c6720a041a7204938cb2db6308b2a4731900731a0001b27204731b0093720be4c6a7070e",
      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "3825b2b4acaaaba626440113153246c65ddb2e9df406c4a56418b5842c9f839a",
          "index": 0,
          "amount": 10000,
          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1a01205589db926e6760d840c919948169a559abcab58ef0d2100126e48f9d2ef12320",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[5589db926e6760d840c919948169a559abcab58ef0d2100126e48f9d2ef12320]"
        },
        "R5": {
          "serializedValue": "1a0120d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de]"
        },
        "R6": {
          "serializedValue": "0e206863b36d721cf7fd4d2a53111c91f1aadb9192bbd7a797dd1f1a49e9f66746f8",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "6863b36d721cf7fd4d2a53111c91f1aadb9192bbd7a797dd1f1a49e9f66746f8"
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        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
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    {
      "boxId": "c442e10bf801c7fa28541963f0484570ad51672e87904a18c511c22e28ae3502",
      "value": 1100000,
      "index": 3,
      "spendingProof": null,
      "outputBlockId": "1113fc5a3c0ec6a706364df3b0b49cc1ddd6c39a6eecc66027ea79b826e89712",
      "outputTransactionId": "4f89a4d3025972a40c83c544bebfaab3669191d549fad7bf7c635a17a2183adf",
      "outputIndex": 1,
      "outputGlobalIndex": 31387038,
      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
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      "assets": [
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          "index": 0,
          "amount": 10000,
          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
        }
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      "additionalRegisters": {
        "R4": {
          "serializedValue": "1a01202228e54299db6c13479c6ced3705df36f2ed0e4e815ed7536ba99be14a13179d",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[2228e54299db6c13479c6ced3705df36f2ed0e4e815ed7536ba99be14a13179d]"
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        "R5": {
          "serializedValue": "1a0120d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de]"
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        "R6": {
          "serializedValue": "0e2008ebe3faa86b77df37c283b7a730f685f28a84f982afa71db0f3735158edc4e0",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "08ebe3faa86b77df37c283b7a730f685f28a84f982afa71db0f3735158edc4e0"
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        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
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      "value": 1100000,
      "index": 4,
      "spendingProof": null,
      "outputBlockId": "1113fc5a3c0ec6a706364df3b0b49cc1ddd6c39a6eecc66027ea79b826e89712",
      "outputTransactionId": "640eadff23a3bc79cb2154597f84707ca4bbfdf49bc6d1be5ec537fe25f5299d",
      "outputIndex": 1,
      "outputGlobalIndex": 31387043,
      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
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          "index": 0,
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          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
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          "serializedValue": "1a0120995ca29a94c2290c7648b56e4a84dafda75765c6e793c5cdcd4fba55ff261e9f",
          "sigmaType": "Coll[Coll[SByte]]",
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      "outputGlobalIndex": 31387048,
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      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
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      "assets": [
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          "index": 0,
          "amount": 10000,
          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
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      "additionalRegisters": {
        "R4": {
          "serializedValue": "1a01208abd3c4a0e14dd3632919a758ccfee875cfcf8ea7e0ec85844d4188834fd602d",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[8abd3c4a0e14dd3632919a758ccfee875cfcf8ea7e0ec85844d4188834fd602d]"
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        "R5": {
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          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de]"
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "4b815f844aca4df6c920887e7e9f1c82fc6f5ac71f0ba688c74865eb72a4df16"
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
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      "spendingProof": null,
      "outputBlockId": "1113fc5a3c0ec6a706364df3b0b49cc1ddd6c39a6eecc66027ea79b826e89712",
      "outputTransactionId": "9bca9cf58998e6f5e8a42d8ec0ba5d2c01fd4f0235542430c247c516a5635d30",
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      "outputGlobalIndex": 31387053,
      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
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          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
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          "sigmaType": "Coll[Coll[SByte]]",
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      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
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      "assets": [
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          "index": 0,
          "amount": 10000,
          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
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      "additionalRegisters": {
        "R4": {
          "serializedValue": "1a0120d050d5e741b9e18bedb81be435f893c8c6ae32ecbbf88554480df8cb9cc0d589",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[d050d5e741b9e18bedb81be435f893c8c6ae32ecbbf88554480df8cb9cc0d589]"
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        "R5": {
          "serializedValue": "1a0120d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de]"
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "eb1e81f72e3992d3f8c03972efdeb3d2aa238da09b3db2ffff3d029aee214449"
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        "R7": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
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      "index": 8,
      "spendingProof": null,
      "outputBlockId": "1113fc5a3c0ec6a706364df3b0b49cc1ddd6c39a6eecc66027ea79b826e89712",
      "outputTransactionId": "c570f52950c1c9f972ebf34a15f4edfec72d5b7ae5a082fcca1929be51dcc5f6",
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      "outputGlobalIndex": 31387063,
      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
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          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
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          "sigmaType": "Coll[Coll[SByte]]",
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      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(66,11,46,-97,-78,-68,-35,-19,-1,101,11,-26,59,26,-53,-62,107,-64,-67,-35,37,91,0,50,80,-121,-86,85,-107,-88,-102,58)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = placeholder[Coll[Byte]](1)\n  val bool3 = blake2b256(box1.propositionBytes) == coll2\n  val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n  val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n  val coll6 = box5.R4[Coll[Coll[Byte]]].get\n  val coll7 = box5.R5[Coll[Coll[Byte]]].get\n  val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n  val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n  val box10 = OUTPUTS(placeholder[Int](5))\n  if (bool3) {(\n    val box11 = OUTPUTS.filter({(box11: Box) =>\n        val opt13 = box11.R4[Coll[Coll[Byte]]]\n        opt13.isDefined && (opt13.get == coll4)\n      })(placeholder[Int](6))\n    val tuple12 = box11.tokens(placeholder[Int](7))\n    val tuple13 = SELF.tokens(placeholder[Int](8))\n    sigmaProp(\n      allOf(\n        Coll[Boolean](\n          blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n            {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n          ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n        )\n      )\n    )\n  )} else {(\n    val coll11 = blake2b256(box10.propositionBytes)\n    if (coll11 == coll2) {(\n      val coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n      val i13 = coll12.size\n      val l14 = i13.toLong\n      val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n      val coll16 = box15.R6[Coll[Long]].get\n      val l17 = coll16(placeholder[Int](11))\n      val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n        Long\n      ](15)\n      val tuple19 = SELF.tokens(placeholder[Int](16))\n      val l20 = coll16(placeholder[Int](17))\n      val tuple21 = box5.tokens(placeholder[Int](18))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n              placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n            ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n              {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n            ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n              Coll[Byte]\n            ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n              l18\n            }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n          )\n        )\n      )\n    )} else {(\n      val tuple12 = box10.tokens(placeholder[Int](23))\n      val tuple13 = SELF.tokens(placeholder[Int](24))\n      sigmaProp(\n        allOf(\n          Coll[Boolean](\n            SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n              placeholder[Int](25)\n            ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n          )\n        )\n      )\n    )}\n  )}\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "3825b2b4acaaaba626440113153246c65ddb2e9df406c4a56418b5842c9f839a",
          "index": 0,
          "amount": 10000,
          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1a0120aba9cf9df2a03cc07c1adc7515d4d70346c93bd7a250525536a90008f73d289d",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[aba9cf9df2a03cc07c1adc7515d4d70346c93bd7a250525536a90008f73d289d]"
        },
        "R5": {
          "serializedValue": "1a0120d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[d9b9dc45aca94c69f3a32b863fd02df939ecf2931de4f3973f6c6e4e3b97e2de]"
        },
        "R6": {
          "serializedValue": "0e207bfb6697ea3d1ddcc34d1b5e36b367f7f311af805bf40ef0e9c9ca8bddf263a1",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "7bfb6697ea3d1ddcc34d1b5e36b367f7f311af805bf40ef0e9c9ca8bddf263a1"
        },
        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
      }
    },
    {
      "boxId": "bfaad3557c2616475a2a7a76bd679f30221593bf1c50813edca91d6f7823ce7e",
      "value": 1987700000,
      "index": 10,
      "spendingProof": "8352438b37ee16c729d2086f2caf67aa11feb2833c0de420e6537f3e756eb89d4b4246febae08f18009e6e4253554ab9d7579237ef6c1344",
      "outputBlockId": "1113fc5a3c0ec6a706364df3b0b49cc1ddd6c39a6eecc66027ea79b826e89712",
      "outputTransactionId": "bf10395093f4e8977e5922f04c1a84e50574b72ad59b1a5ca4fc3a42b172116c",
      "outputIndex": 2,
      "outputGlobalIndex": 31387059,
      "outputCreatedAt": 1058175,
      "outputSettledAt": 1058178,
      "ergoTree": "0008cd030467e8dcb02d687b1f43da1c9dccea7e92affa6024a9bcd66e1ba74763210749",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(467e8d,1dadce,...)))}",
      "address": "9gVkEXyFWKGkmJKqTVvy4Qmv3A2BSEhNjTUjYzjBKxorVvELWRu",
      "assets": [
        {
          "tokenId": "d050d5e741b9e18bedb81be435f893c8c6ae32ecbbf88554480df8cb9cc0d589",
          "index": 0,
          "amount": 1,
          "name": null,
          "decimals": null,
          "type": null
        }
      ],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [
    {
      "boxId": "8531bdff9172c4897a9806b82186b7785130f666528f6da4e3f72858ee22081f",
      "value": 1100000,
      "index": 0,
      "outputBlockId": "e29988c2e0cd821fc0c44cc2e501372bc36576836c8c5979e0d05b2e7418d83d",
      "outputTransactionId": "94a4553c69c53af44b5a1d87050b37326b5bde6420a45f01cda3955779ab2d36",
      "outputIndex": 0,
      "ergoTree": "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",
      "address": "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",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "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",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[6572676f,e61a83c5bca59e98c21d925faff5dfc079aa438f21df08702e4c4bf2bada02dc,d050d5e741b9e18bedb81be435f893c8c6ae32ecbbf88554480df8cb9cc0d589,995ca29a94c2290c7648b56e4a84dafda75765c6e793c5cdcd4fba55ff261e9f,90829fb915dba5c834d14b0e1e1387f6c2e4760965b8cd338892e4ad13baab3d,fe83cb8a2843fa6f5751d65e4f957fc622c67ab9211f30b44991a1fb03145c01,8abd3c4a0e14dd3632919a758ccfee875cfcf8ea7e0ec85844d4188834fd602d,3d36709eb83dc46cc60298ab183a1e4ab1d85363337b951b9494dc1ab1418eb1,5589db926e6760d840c919948169a559abcab58ef0d2100126e48f9d2ef12320,aba9cf9df2a03cc07c1adc7515d4d70346c93bd7a250525536a90008f73d289d,2228e54299db6c13479c6ced3705df36f2ed0e4e815ed7536ba99be14a13179d]"
        },
        "R5": {
          "serializedValue": "110b0080dac40980dac40980dac40980dac40980dac40980dac40980dac40980dac40980dac40980dac409",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[0,10000000,10000000,10000000,10000000,10000000,10000000,10000000,10000000,10000000,10000000]"
        },
        "R6": {
          "serializedValue": "1106a09c018c01022880a8d6b90700",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000,70,1,20,1000000000,0]"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "4ac971c3faec33e1789cf45f59f4595a10ddeae178a04e1a49dc3c81b3f998ea",
      "transactionId": "10434ecbd9595f9955947eb70920d098e7a4d520e8577f70fc4a59901eb7c873",
      "blockId": "99b7828ca5d99cafbb88c9de991a79dc46d9955a5d97ca2b70fee1ebbf25c5bb",
      "value": 11000000,
      "index": 0,
      "globalIndex": 31388289,
      "creationHeight": 1058188,
      "settlementHeight": 1058190,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: Coll(-114,30,-46,70,96,13,44,-117,-112,95,56,-10,96,-39,72,0,108,-53,-91,-43,22,45,-64,37,-98,-83,-5,120,68,69,-3,-55)\n7: 1\n8: 0\n9: Coll(-28,-36,-91,-57,-77,94,-83,20,-26,86,-103,80,91,-35,101,-81,92,0,-78,36,-109,39,-32,-19,-101,-96,-30,-75,9,16,26,-126)\n10: 7200\n11: Coll(70,36,70,31,-62,-119,64,54,-23,-68,80,103,-65,-15,-28,103,-108,42,-46,-17,42,-11,33,-114,-92,83,108,-75,23,-64,14,43)",
      "ergoTreeScript": "{\n  val coll1 = SELF.R4[Coll[Coll[Byte]]].get\n  val i2 = coll1.size\n  val coll3 = OUTPUTS.slice(placeholder[Int](0), i2)\n  val coll4 = OUTPUTS(placeholder[Int](1)).propositionBytes\n  val coll5 = blake2b256(coll4)\n  sigmaProp(allOf(Coll[Boolean](i2 == coll3.size, coll1.zip(coll3).forall({(tuple6: (Coll[Byte], Box)) =>\n            val box8 = tuple6._2\n            (((Coll[Coll[Byte]](tuple6._1) == box8.R4[Coll[Coll[Byte]]].get) && (box8.propositionBytes == coll4)) && (box8.tokens(placeholder[Int](2))._1 == SELF.tokens(placeholder[Int](3))._1)) && (box8.tokens(placeholder[Int](4))._2 == SELF.tokens(placeholder[Int](5))._2 / i2.toLong)\n          }), if (coll5 == placeholder[Coll[Byte]](6)) { allOf(Coll[Boolean](INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == placeholder[Coll[Byte]](9), HEIGHT - placeholder[Int](10) >= SELF.creationInfo._1)) } else { allOf(Coll[Boolean](INPUTS.exists({(box6: Box) => blake2b256(box6.propositionBytes) == placeholder[Coll[Byte]](11) }), coll5 == SELF.R6[Coll[Byte]].get)) })))\n}",
      "address": "BRNzuPCshtnBeoxCJ8iQiVbfd6yZNTf3KfxSfpsfDeC18pKRVoNNgDUo91X8TQRdLcnRwFHCU7doEUu4vciu5sfQbKyyd5FQD2x4X24eJFyR52vTtE4sVP46utpskdbwB9C3By3ueXBuDF6gmT6o83tN5b9wPjXtdpJowqgu2ZLDruYsqEdrPgGLsE1rfvBJM2NCYH9Gcp2UvJSGMiCu1p4XiLg1HpFhvcUz4wFwYFPBdUwoZVjERf6VVHv2hWzybdfxLBSEBPGys9xLPX4ck8Ms2LgBdX9GsAiXDnmrJ4A1NHqbJUZzUBfHEBUUUR94nJCoGfyAaFvDBafbouRuxe1MkArntvv6j6CQYe436e4hfZmrnC8aHGUaMvXQjtCwp4sF3yXe6c7Gf8GKw9LT1Tsk6AbMy4nP1X8jmaztJJhc8f7yopXSPEGM7JyNBNHyvp",
      "assets": [
        {
          "tokenId": "3825b2b4acaaaba626440113153246c65ddb2e9df406c4a56418b5842c9f839a",
          "index": 0,
          "amount": 100000,
          "name": "rptconfErgoRWTV1",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "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",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[90829fb915dba5c834d14b0e1e1387f6c2e4760965b8cd338892e4ad13baab3d,e61a83c5bca59e98c21d925faff5dfc079aa438f21df08702e4c4bf2bada02dc,5589db926e6760d840c919948169a559abcab58ef0d2100126e48f9d2ef12320,2228e54299db6c13479c6ced3705df36f2ed0e4e815ed7536ba99be14a13179d,995ca29a94c2290c7648b56e4a84dafda75765c6e793c5cdcd4fba55ff261e9f,8abd3c4a0e14dd3632919a758ccfee875cfcf8ea7e0ec85844d4188834fd602d,3d36709eb83dc46cc60298ab183a1e4ab1d85363337b951b9494dc1ab1418eb1,d050d5e741b9e18bedb81be435f893c8c6ae32ecbbf88554480df8cb9cc0d589,fe83cb8a2843fa6f5751d65e4f957fc622c67ab9211f30b44991a1fb03145c01,aba9cf9df2a03cc07c1adc7515d4d70346c93bd7a250525536a90008f73d289d]"
        },
        "R5": {
          "serializedValue": "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",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[33333164396663353635646534346233383430626365373063623731316333336163303239623833383832653133316338336537363762323463666161646339,6572676f,63617264616e6f,396763724b6e374c354c6e337252736a466f53456b45736f76556462354a523564366f327648515635464358584e6b6b454144,616464723171396e77676c6c6c74376a3030796634307776656163327467746d787879377930366e74757273366c3833776e39673337646a6c6e7a35686d6d6d6b78656e786c386d77716c366839366775377a74706867786a66306e67776866717761646d3764,00000000b2d05e00,0000000077359400,000000002faf0800,657267,61737365743132647a63796c6d6579386d7a7166346c7178376c7533746c6e657677727471347675726a3832,39353639326665623864633162366363306631643334323536303032383931336230653263316132356362396335623663386261636632303537663030323832,000000000010256f]"
        },
        "R6": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
      },
      "spentTransactionId": "132c642fb871a3cf757a9c0a5aa40ac39c10004ccd3131e2c14a7fe9fc66073a",
      "mainChain": true
    },
    {
      "boxId": "cdc06c2f8c7b008fedebd729d5da1a8118d148e38d1454e7d171a9c4f58f128b",
      "transactionId": "10434ecbd9595f9955947eb70920d098e7a4d520e8577f70fc4a59901eb7c873",
      "blockId": "99b7828ca5d99cafbb88c9de991a79dc46d9955a5d97ca2b70fee1ebbf25c5bb",
      "value": 1986600000,
      "index": 1,
      "globalIndex": 31388290,
      "creationHeight": 1058188,
      "settlementHeight": 1058190,
      "ergoTree": "0008cd030467e8dcb02d687b1f43da1c9dccea7e92affa6024a9bcd66e1ba74763210749",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(467e8d,1dadce,...)))}",
      "address": "9gVkEXyFWKGkmJKqTVvy4Qmv3A2BSEhNjTUjYzjBKxorVvELWRu",
      "assets": [
        {
          "tokenId": "d050d5e741b9e18bedb81be435f893c8c6ae32ecbbf88554480df8cb9cc0d589",
          "index": 0,
          "amount": 1,
          "name": null,
          "decimals": null,
          "type": null
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "215bc219ea07e61d268f2766c29e3dde516c129938354e9ec172a541e26cc21f",
      "mainChain": true
    },
    {
      "boxId": "7358105e7ec37199fec178e6a3d6cd3f2226fde68e118517da7c04d528176692",
      "transactionId": "10434ecbd9595f9955947eb70920d098e7a4d520e8577f70fc4a59901eb7c873",
      "blockId": "99b7828ca5d99cafbb88c9de991a79dc46d9955a5d97ca2b70fee1ebbf25c5bb",
      "value": 1100000,
      "index": 2,
      "globalIndex": 31388291,
      "creationHeight": 1058188,
      "settlementHeight": 1058190,
      "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": "760c4e747dd5d022b71aedec5638a99497440e1de964c3a8dc497911146bd0b4",
      "mainChain": true
    }
  ],
  "size": 1781,
  "isUnconfirmed": false
}