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Transaction

7/24/2023 08:47:39 AM
ID: 8fed243091...eb14
Inputs (11)
#0
852b31c585af...7cf3
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
1f33b7820af3...d2a7
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#1
93db076b585c...216e
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
23c441a1d132...87a4
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#2
a4765424a491...a0bc
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
4b17c48b4e48...9361
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#3
bd089b948776...9012
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
51a0d1f6025e...c1a7
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#4
a5da6554f893...a1aa
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
56a5541cf2d3...536f
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#5
cc831022c031...f236
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
b026f2eccfea...4590
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#6
e3c8e3d158e3...9ade
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
d32fb57012ed...b453
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#7
dc5de762a999...3bc9
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
e43015a08c64...68df
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#8
51d6a3b33a80...ebc8
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
ede167340c53...8044
Settlement height:
1,053,311
Value:
0.0011 ERG
Tokens:
Loading assets...
#9
34b0940d2cda...4f2d
Spent
Address:
4YCK14N7W9Yb...fCDd
Output transaction:
3d1b4011e873...37fa
Settlement height:
1,053,313
Value:
0.0011 ERG
Tokens:
Loading assets...
#10
80fccd02b296...b207
Spent
Address:
9fGuR8wsLfdW...jXMw
Output transaction:
03bd6e35c9a1...0f54
Settlement height:
1,044,842
Value:
1 ERG
Tokens:
rptconfRSNV1
20
Outputs (3)
#0
da5059b8a4aa...cde6
Spent
Address:
BRNzuPCshtnB...Hyvp
Spent in transaction:
594fc85bf522...a262
Settlement height:
1,053,870
Value:
0.011 ERG
Tokens:
Loading assets...
#1
318b15dd5b97...b345
Spent
Address:
9fGuR8wsLfdW...jXMw
Spent in transaction:
a7a78bc3a43e...9b1c
Settlement height:
1,053,870
Value:
0.9989 ERG
Tokens:
rptconfRSNV1
20
#2
e17245e41e79...ed12
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
0da4d2294ff9...70a3
Settlement height:
1,053,870
Value:
0.0011 ERG
Transaction Details
Status: Confirmed
Size: 1.74 KB
Received time: 7/24/2023 08:47:39 AM
Included in blocks: 1,053,870
Confirmations: 714,117
Total coins transferred: 1.01 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000617 ERG
Raw Transaction Data
{
  "id": "8fed243091d1c43eeb05ed8ae808fea902e06fdcac1c1e26f36923792a3feb14",
  "blockId": "27310f7b84c2918eccd51d0bf4814fd3e6d819bd5ce32538ebffafadb01c0ff5",
  "inclusionHeight": 1053870,
  "timestamp": 1690188459051,
  "index": 2,
  "globalIndex": 5562286,
  "numConfirmations": 714117,
  "inputs": [
    {
      "boxId": "852b31c585af14370276aed767c2be04e07eafdfdf382d3126933e89bad77cf3",
      "value": 1100000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "7c4607b8e924816c68583a3f7a12c4c030a302b3941f0d17c15d75cd170e903e",
      "outputTransactionId": "1f33b7820af346095d16fd242c1b0a659cf0423b96482e639d998ddf4e72d2a7",
      "outputIndex": 1,
      "outputGlobalIndex": 31186620,
      "outputCreatedAt": 1053307,
      "outputSettledAt": 1053311,
      "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": "1a0120995ca29a94c2290c7648b56e4a84dafda75765c6e793c5cdcd4fba55ff261e9f",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[995ca29a94c2290c7648b56e4a84dafda75765c6e793c5cdcd4fba55ff261e9f]"
        },
        "R5": {
          "serializedValue": "1a0120c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848]"
        },
        "R6": {
          "serializedValue": "0e2036713800992a898d91f106ad584be287a4085c8b5822f0bdecddd0acb41b540a",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "36713800992a898d91f106ad584be287a4085c8b5822f0bdecddd0acb41b540a"
        },
        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
      }
    },
    {
      "boxId": "93db076b585c74cdec82de949f91a9359d5ee55828de16ecb6ce2f2dd2d9216e",
      "value": 1100000,
      "index": 1,
      "spendingProof": null,
      "outputBlockId": "7c4607b8e924816c68583a3f7a12c4c030a302b3941f0d17c15d75cd170e903e",
      "outputTransactionId": "23c441a1d1328a2f769e7d388bf5df179aef6e6fe43b0385f075cd4b8ba287a4",
      "outputIndex": 1,
      "outputGlobalIndex": 31186624,
      "outputCreatedAt": 1053307,
      "outputSettledAt": 1053311,
      "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": "1a0120fe83cb8a2843fa6f5751d65e4f957fc622c67ab9211f30b44991a1fb03145c01",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[fe83cb8a2843fa6f5751d65e4f957fc622c67ab9211f30b44991a1fb03145c01]"
        },
        "R5": {
          "serializedValue": "1a0120c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848]"
        },
        "R6": {
          "serializedValue": "0e20c6d9de63fd56c4fcb3bac42f3e542f97efa834454256df9baeada9c58f7b346f",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "c6d9de63fd56c4fcb3bac42f3e542f97efa834454256df9baeada9c58f7b346f"
        },
        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
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    },
    {
      "boxId": "a4765424a4918d6dbb2896fe796082e64113c331c0c41087bc1860f99b38a0bc",
      "value": 1100000,
      "index": 2,
      "spendingProof": null,
      "outputBlockId": "7c4607b8e924816c68583a3f7a12c4c030a302b3941f0d17c15d75cd170e903e",
      "outputTransactionId": "4b17c48b4e48ef765f55d05ccfe6b379c00eb0a08e0183687753063d8dd79361",
      "outputIndex": 1,
      "outputGlobalIndex": 31186628,
      "outputCreatedAt": 1053307,
      "outputSettledAt": 1053311,
      "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": "1a0120e61a83c5bca59e98c21d925faff5dfc079aa438f21df08702e4c4bf2bada02dc",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[e61a83c5bca59e98c21d925faff5dfc079aa438f21df08702e4c4bf2bada02dc]"
        },
        "R5": {
          "serializedValue": "1a0120c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848]"
        },
        "R6": {
          "serializedValue": "0e2014f231dfe26adcd51bdeb50fcfda5a31505920323ee10abdb95a8c4aa39af97a",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "14f231dfe26adcd51bdeb50fcfda5a31505920323ee10abdb95a8c4aa39af97a"
        },
        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
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      "value": 1100000,
      "index": 3,
      "spendingProof": null,
      "outputBlockId": "7c4607b8e924816c68583a3f7a12c4c030a302b3941f0d17c15d75cd170e903e",
      "outputTransactionId": "51a0d1f6025eacc70005d5311f9c80d3835d940a3eed254789361cef81fdc1a7",
      "outputIndex": 1,
      "outputGlobalIndex": 31186632,
      "outputCreatedAt": 1053307,
      "outputSettledAt": 1053311,
      "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"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1a012090829fb915dba5c834d14b0e1e1387f6c2e4760965b8cd338892e4ad13baab3d",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[90829fb915dba5c834d14b0e1e1387f6c2e4760965b8cd338892e4ad13baab3d]"
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        "R5": {
          "serializedValue": "1a0120c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848]"
        },
        "R6": {
          "serializedValue": "0e20e837a436665f810e9c0995dd05813fe303773e512cdb173ddc889c0e17100353",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "e837a436665f810e9c0995dd05813fe303773e512cdb173ddc889c0e17100353"
        },
        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
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      "value": 1100000,
      "index": 4,
      "spendingProof": null,
      "outputBlockId": "7c4607b8e924816c68583a3f7a12c4c030a302b3941f0d17c15d75cd170e903e",
      "outputTransactionId": "56a5541cf2d35e8f0b5477d58d29473e35625714ea73d85824ac1d4f6684536f",
      "outputIndex": 1,
      "outputGlobalIndex": 31186636,
      "outputCreatedAt": 1053307,
      "outputSettledAt": 1053311,
      "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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        "R4": {
          "serializedValue": "1a01203d36709eb83dc46cc60298ab183a1e4ab1d85363337b951b9494dc1ab1418eb1",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[3d36709eb83dc46cc60298ab183a1e4ab1d85363337b951b9494dc1ab1418eb1]"
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          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848]"
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          "serializedValue": "0e206a63e0cbe34ccef619c0d275fdf517d5159bfa5af7399bdb90e9b1b97fe56c14",
          "sigmaType": "Coll[SByte]",
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          "sigmaType": "Coll[SByte]",
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      "spendingProof": null,
      "outputBlockId": "7c4607b8e924816c68583a3f7a12c4c030a302b3941f0d17c15d75cd170e903e",
      "outputTransactionId": "b026f2eccfeac54d173a8df279b67be164f5ac7da380c030101187e9b1274590",
      "outputIndex": 1,
      "outputGlobalIndex": 31186640,
      "outputCreatedAt": 1053307,
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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": {
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          "serializedValue": "1a0120aba9cf9df2a03cc07c1adc7515d4d70346c93bd7a250525536a90008f73d289d",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[aba9cf9df2a03cc07c1adc7515d4d70346c93bd7a250525536a90008f73d289d]"
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        "R5": {
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          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848]"
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        "R6": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "80d7ae4a0abf8b6038c014c0e95d77f8d13991e9688f2e0becc219271f3f70b2"
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        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
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      "spendingProof": null,
      "outputBlockId": "7c4607b8e924816c68583a3f7a12c4c030a302b3941f0d17c15d75cd170e903e",
      "outputTransactionId": "d32fb57012edcb91edbca473ce841ba76ed5155823a65dc76c916414ba4cb453",
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      "outputGlobalIndex": 31186644,
      "outputCreatedAt": 1053307,
      "outputSettledAt": 1053311,
      "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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          "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": {
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          "serializedValue": "1a01205589db926e6760d840c919948169a559abcab58ef0d2100126e48f9d2ef12320",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[5589db926e6760d840c919948169a559abcab58ef0d2100126e48f9d2ef12320]"
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        "R5": {
          "serializedValue": "1a0120c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848]"
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        "R6": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "7c0e44a1605177e8773015684b3d4462f5df6a0ab12dbe4cc4cd94369f0f00a5"
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        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
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      "spendingProof": null,
      "outputBlockId": "7c4607b8e924816c68583a3f7a12c4c030a302b3941f0d17c15d75cd170e903e",
      "outputTransactionId": "ede167340c5384bcf3360e644a5eadb46ed29e33bd72c1da2f80480f11938044",
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      "outputGlobalIndex": 31186652,
      "outputCreatedAt": 1053307,
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      "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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          "sigmaType": "Coll[Coll[SByte]]",
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      "outputCreatedAt": 1053307,
      "outputSettledAt": 1053313,
      "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": "1a01202228e54299db6c13479c6ced3705df36f2ed0e4e815ed7536ba99be14a13179d",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[2228e54299db6c13479c6ced3705df36f2ed0e4e815ed7536ba99be14a13179d]"
        },
        "R5": {
          "serializedValue": "1a0120c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[c070f39a07ef3899203e92bb049298cf864c9cd567cb576a060a952f5b013848]"
        },
        "R6": {
          "serializedValue": "0e206bfe126ec6b48f9111ac462946f8e256b14bfffcb83f681e81e629784a9f2ad1",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "6bfe126ec6b48f9111ac462946f8e256b14bfffcb83f681e81e629784a9f2ad1"
        },
        "R7": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
      }
    },
    {
      "boxId": "80fccd02b29624b5e999ffc85b44c50637fa742d37a5b770e17d256836d1b207",
      "value": 1000000000,
      "index": 10,
      "spendingProof": "91b90f16deefdd7b15e5f3670cc7a057a2e4fd2365de9d98101f50ce339aee5c22a95abe21e1716394ce27ff4185f0833d3611f6ab2e18bb",
      "outputBlockId": "89c9a6a386b3c11eb9d0580e3ba5b9126c145475c6b9884219339601fa0f7045",
      "outputTransactionId": "03bd6e35c9a18a0a06b1789652403d2adbfa981f162a83042c13099f23bf0f54",
      "outputIndex": 2,
      "outputGlobalIndex": 30857689,
      "outputCreatedAt": 1044840,
      "outputSettledAt": 1044842,
      "ergoTree": "0008cd02638d1bd6fa628630b5fc668b06a6a1b398be1c8de8234b232e2913c21df675cd",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(638d1b,f156dd,...)))}",
      "address": "9fGuR8wsLfdWVjWkn9extivJ5vY56vdRi4VSWF66ymKexNUjXMw",
      "assets": [
        {
          "tokenId": "f8fe64d3d94d4eb193ea9d6304646db67bd914ed42cebd3a4f614d9d9de75cf0",
          "index": 0,
          "amount": 20000,
          "name": "rptconfRSNV1",
          "decimals": 3,
          "type": "EIP-004"
        }
      ],
      "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": "da5059b8a4aa75dcbbeaef53781489ae92803043e7aa9d4f6ddb9927fb16cde6",
      "transactionId": "8fed243091d1c43eeb05ed8ae808fea902e06fdcac1c1e26f36923792a3feb14",
      "blockId": "27310f7b84c2918eccd51d0bf4814fd3e6d819bd5ce32538ebffafadb01c0ff5",
      "value": 11000000,
      "index": 0,
      "globalIndex": 31212602,
      "creationHeight": 1053867,
      "settlementHeight": 1053870,
      "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": "[995ca29a94c2290c7648b56e4a84dafda75765c6e793c5cdcd4fba55ff261e9f,fe83cb8a2843fa6f5751d65e4f957fc622c67ab9211f30b44991a1fb03145c01,e61a83c5bca59e98c21d925faff5dfc079aa438f21df08702e4c4bf2bada02dc,90829fb915dba5c834d14b0e1e1387f6c2e4760965b8cd338892e4ad13baab3d,3d36709eb83dc46cc60298ab183a1e4ab1d85363337b951b9494dc1ab1418eb1,aba9cf9df2a03cc07c1adc7515d4d70346c93bd7a250525536a90008f73d289d,d050d5e741b9e18bedb81be435f893c8c6ae32ecbbf88554480df8cb9cc0d589,5589db926e6760d840c919948169a559abcab58ef0d2100126e48f9d2ef12320,8abd3c4a0e14dd3632919a758ccfee875cfcf8ea7e0ec85844d4188834fd602d,2228e54299db6c13479c6ced3705df36f2ed0e4e815ed7536ba99be14a13179d]"
        },
        "R5": {
          "serializedValue": "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",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[31613234373737316137633534323165313762363736346331333863323762663262343961323331353235393033653363323431656661356334663863623863,6572676f,63617264616e6f,396763724b6e374c354c6e337252736a466f53456b45736f76556462354a523564366f327648515635464358584e6b6b454144,616464723171396e77676c6c6c74376a3030796634307776656163327467746d787879377930366e74757273366c3833776e39673337646a6c6e7a35686d6d6d6b78656e786c386d77716c366839366775377a74706867786a66306e67776866717761646d3764,000000003b9aca00,0000000009d5b340,0000000003ef1480,657267,61737365743132647a63796c6d6579386d7a7166346c7178376c7533746c6e657677727471347675726a3832,65356230656365636133313731386436326539656337386431633638323331663361376639366465613736396562666335383538643263313534656138633237,0000000000101269]"
        },
        "R6": {
          "serializedValue": "0e20aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "aedb01e6a2594d7dacf6f63b2f3247e3b1ecf01409960758934d2fb4c3004f07"
        }
      },
      "spentTransactionId": "594fc85bf522a2c03bc952a2f97eb84245bdb4788ccf230d4e863db2d5f8a262",
      "mainChain": true
    },
    {
      "boxId": "318b15dd5b9789d95c7a3031017bc475a2cd88c3b2d39529669d3ca14043b345",
      "transactionId": "8fed243091d1c43eeb05ed8ae808fea902e06fdcac1c1e26f36923792a3feb14",
      "blockId": "27310f7b84c2918eccd51d0bf4814fd3e6d819bd5ce32538ebffafadb01c0ff5",
      "value": 998900000,
      "index": 1,
      "globalIndex": 31212603,
      "creationHeight": 1053867,
      "settlementHeight": 1053870,
      "ergoTree": "0008cd02638d1bd6fa628630b5fc668b06a6a1b398be1c8de8234b232e2913c21df675cd",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(638d1b,f156dd,...)))}",
      "address": "9fGuR8wsLfdWVjWkn9extivJ5vY56vdRi4VSWF66ymKexNUjXMw",
      "assets": [
        {
          "tokenId": "f8fe64d3d94d4eb193ea9d6304646db67bd914ed42cebd3a4f614d9d9de75cf0",
          "index": 0,
          "amount": 20000,
          "name": "rptconfRSNV1",
          "decimals": 3,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "a7a78bc3a43edc94d959d7f5cf8ee610ab7165910a0831e363a0977ff9359b1c",
      "mainChain": true
    },
    {
      "boxId": "e17245e41e79b1a5c355449e61c997d74287963c98d13bdfda7b4a3fb918ed12",
      "transactionId": "8fed243091d1c43eeb05ed8ae808fea902e06fdcac1c1e26f36923792a3feb14",
      "blockId": "27310f7b84c2918eccd51d0bf4814fd3e6d819bd5ce32538ebffafadb01c0ff5",
      "value": 1100000,
      "index": 2,
      "globalIndex": 31212604,
      "creationHeight": 1053867,
      "settlementHeight": 1053870,
      "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": "0da4d2294ff9e7cfd9592f599ae1e55cf160a7ea79339dc4a68ffb5ff7e670a3",
      "mainChain": true
    }
  ],
  "size": 1783,
  "isUnconfirmed": false
}