Ad
Inputs (1)
Output transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
Loading assets...
Outputs (11)
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Transaction Details
Status: Confirmed
Size: 13.36 KB
Received time: 2/23/2026 01:28:17 PM
Included in blocks: 1,728,252
Confirmations: 41,727
Total coins transferred: 0.011 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000073 ERG
Raw Transaction Data
{
  "id": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
  "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
  "inclusionHeight": 1728252,
  "timestamp": 1771853297902,
  "index": 16,
  "globalIndex": 10347631,
  "numConfirmations": 41727,
  "inputs": [
    {
      "boxId": "c49baa712cd7542bf9bea72e6ab6495b26ca5190832798b2b050b51dbaf4bca8",
      "value": 11000000,
      "index": 0,
      "spendingProof": "720f8d1f1c342dd5dd9b5dcf844381c00fb79738b9a6f784cf217aac891a65179576ee46f975a51b0195ba7b5369aac5005270b2d3f33d06",
      "outputBlockId": "ab8d29b15d6cc32dca2cc03d79bb92b677fb4de09702e519888e26d41b741a70",
      "outputTransactionId": "b9a3f5650dac5f85f6893b5c4b577ab5a0001f4ed28986c59ea236ed0e1a8c41",
      "outputIndex": 0,
      "outputGlobalIndex": 53757474,
      "outputCreatedAt": 1728247,
      "outputSettledAt": 1728249,
      "ergoTree": "100204b82408cd03199bd9865508d9e9c998e828d8313cb1bf83d43ac79c467d33f8d1223fde382cea02d191a373007301",
      "ergoTreeConstants": "0: 2332\n1: SigmaProp(ProveDlog(ECPoint(199bd9,a14ea8,...)))",
      "ergoTreeScript": "{sigmaProp(HEIGHT > placeholder[Int](0)) && placeholder[SigmaProp](1)}",
      "address": "FKdveq41wjvMz6gTSGNeCKVDvaEMZcDuMdwM6rpFt3S1J7JkRDKEckHfGz7aPGpisNgeENAbo",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 10,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e114c6f676963204e4654204552472d322e30",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "4c6f676963204e4654204552472d322e30"
        },
        "R5": {
          "serializedValue": "0e236475636b706f6f6c73207632204c6f676963204e465420666f722045524720706f6f6c",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "6475636b706f6f6c73207632204c6f676963204e465420666f722045524720706f6f6c"
        },
        "R6": {
          "serializedValue": "0e0130",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "30"
        }
      }
    }
  ],
  "dataInputs": [],
  "outputs": [
    {
      "boxId": "622f0ebcb3c0facd872c311e5ec65461604c38da10dfccc7717b42eee81eaa04",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 0,
      "globalIndex": 53757664,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "f3c614ac6032cc4366b2b16553b67484fd3616de452ca5a09379a284b28445bd",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 1,
      "globalIndex": 53757665,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "103f0400040004000400040004080408040a040a040c040c04100410040e040e0402040004000402040104020402060100060102060164060203e8050004040480ade2040580c0a8ca9a3a0402050008cd03dda8fe44b65ff96eb9dd442e6f10aca93f7351e96f2cbb1862c21a9055bc8b9604040402040605d00f0500053c0400050004040402040405d20f04020400040405000402040005000580a4e8030502050005d00f0500050004120412050004000400d82cd601c2a7d602b2b5a5d9010263d801d604db63087202ed91b17204730093b27204730100b2db6308a7730200730300d603c27202d604e4c672020411d605b27204730400d606e4c6a70411d607b27206730500d608b27204730600d609b27206730700d60ab27204730800d60bb27206730900d60cb27204730a00d60db27206730b00d60eb27204730c00d60fb27206730d00d610b27204730e00d611e4c6a7051ad612e4c67202051ad613e4c6a70611d614e4c672020611d615db6501fed616e4c672020910d617b27216730f00d618b27215721700d619db63087218d61ab27216731000d61b9591721a7311b2a599721a731200b2a4999c721a7313731400d61c7ec1721b06d61db472159a72177315b17215d61ee4c672020711d61f7316d6207317d6217318d6227319d623999a721cb0dc0c1d721d01721e721fd90123424d63d804d6258c722302d6268c722502d6278c722501d6288c72230195917226731ad803d6297e722606d62a7ee4c67227040406d62b7e8cb2db63087227731b0002069a72289d9c9c7ec17227067229722a9a9c9a722b9d9c722b7220722172229c7229722a72287e731c06d6247ee4c67218040406d6257ec1721806d626731dd627db6308721bd628b17227d629e4c67202081ad62ab47212731eb17212d62bb1721dd62cb1721eeb02ea02d1edededededededededed937201720393c1a7c1720293db6308a7db63087202937205731f9372077208937209720a93720b720c93720d720e93720f7210937211721293721372147320d1ededededededededededededededededed9372037201ed93721272119372147213939d9c9c7e8cb272197321000206722372249a9c9a72259d9c72257220722172229c722372247eb272047322000693a2a1b27204732300732473257326939d9a9d9c9c721c7e7226067eb27214732700067223b0db0c0e721e721fd9012d4204d803d62f8c722d02d630b2721e722f00d6318c722d01959172307328d804d632b2721d722f00d6337e723006d6347ee4c67232040406d6357e8cb2db6308723273290002069a72319d9c9c9d9c9c7ec1723206723372349a9c9a72359d9c72357220722172229c723372347e7226067eb2b47214732ab17214722f0006722372317e7226067ea2b27204732b00732c06afb47227732d7228d9012d4d0eaedc0c1d722901721ed9012f4d0e93722f722dafdb0c0e722ad9012d04d801d62fdb6308b2721d722d00ed93b2722a722d008cb2722f732e000193b27229722d008cb2722f732f0001ed93722b722c93722bb1722a93722cb1722993b1b5721ed9012d0593722d733099722c997228733193b27206733200a272057333937207a272087334937209a2720a733593720ba2720c733693720fa2a172107337733893720da2720e733993b27206733a00a2b27204733b00733c938cb27219733d0001b27212733e00",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "f322ffeb476231bf153f360867510bc6fb098da57465de64b47b17b382970127",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 2,
      "globalIndex": 53757666,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "2e72c0a1a5e3e2a953b4e7d50d1ecd33fd26876f3371ee433e16f40c3c719973",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 3,
      "globalIndex": 53757667,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "fd45c0a812eebca72026aa41b04d837abee8c0d7fe1506437140162cb6b8fd11",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 4,
      "globalIndex": 53757668,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "245b7b0ea7d9c1606efbf25d0af438010a4cd5e1a8d57983a84de00e70714b90",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 5,
      "globalIndex": 53757669,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "623ec309dd0c322ebc6b9bd10dcd05b6d31d659e00f532b06916520e88639145",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 6,
      "globalIndex": 53757670,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "4e6dc077ff6a812babb9aa7b5260ce417035122d9f1c7a45237509d181ff2ea3",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 7,
      "globalIndex": 53757671,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "a3dd19dc8005f8d6e3138ca7f0f644771e52bcb0056bbe0593817b53598f8d10",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 8,
      "globalIndex": 53757672,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": null,
      "mainChain": true
    },
    {
      "boxId": "55318255d4d6ca51202d9c4871aa928976db4fa04c12b847aac834710c0710b5",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 9,
      "globalIndex": 53757673,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
      "ergoTreeScript": "{\n  val coll1 = SELF.propositionBytes\n  val box2 = OUTPUTS.filter({(box2: Box) =>\n      val coll4 = box2.tokens\n      (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n    })(placeholder[Int](3))\n  val coll3 = box2.propositionBytes\n  val coll4 = box2.R4[Coll[Long]].get\n  val l5 = coll4(placeholder[Int](4))\n  val coll6 = SELF.R4[Coll[Long]].get\n  val l7 = coll6(placeholder[Int](5))\n  val l8 = coll4(placeholder[Int](6))\n  val l9 = coll6(placeholder[Int](7))\n  val l10 = coll4(placeholder[Int](8))\n  val l11 = coll6(placeholder[Int](9))\n  val l12 = coll4(placeholder[Int](10))\n  val l13 = coll6(placeholder[Int](11))\n  val l14 = coll4(placeholder[Int](12))\n  val l15 = coll6(placeholder[Int](13))\n  val l16 = coll4(placeholder[Int](14))\n  val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n  val coll18 = box2.R5[Coll[Coll[Byte]]].get\n  val coll19 = SELF.R6[Coll[Long]].get\n  val coll20 = box2.R6[Coll[Long]].get\n  val coll21 = CONTEXT.dataInputs\n  val coll22 = box2.R9[Coll[Int]].get\n  val i23 = coll22(placeholder[Int](15))\n  val box24 = coll21(i23)\n  val coll25 = box24.tokens\n  val i26 = coll22(placeholder[Int](16))\n  val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n  val bi28 = box27.value.toBigInt\n  val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n  val coll30 = box2.R7[Coll[Long]].get\n  val bi31 = placeholder[BigInt](22)\n  val bi32 = placeholder[BigInt](23)\n  val bi33 = placeholder[BigInt](24)\n  val bi34 = placeholder[BigInt](25)\n  val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n      val tuple37 = tuple35._2\n      val l38 = tuple37._2\n      val box39 = tuple37._1\n      val bi40 = tuple35._1\n      if (l38 > placeholder[Long](26)) {(\n        val bi41 = l38.toBigInt\n        val bi42 = box39.R4[Int].get.toBigInt\n        val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n        bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n      )} else { bi40 }\n    }) - placeholder[Int](28).toBigInt\n  val bi36 = box24.R4[Int].get.toBigInt\n  val bi37 = box24.value.toBigInt\n  val l38 = placeholder[Long](29)\n  val coll39 = box27.tokens\n  val i40 = coll39.size\n  val coll41 = box2.R8[Coll[Coll[Byte]]].get\n  val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n  val i43 = coll29.size\n  val i44 = coll30.size\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n                l9 == l10\n              )\n            ) && (l11 == l12)\n          ) && (l13 == l14)\n        ) && (l15 == l16)\n      ) && (coll17 == coll18)\n    ) && (coll19 == coll20)\n  ) && placeholder[SigmaProp](32) || sigmaProp(\n    (\n      (\n        (\n          (\n            (\n              (\n                (\n                  (\n                    (\n                      (\n                        (\n                          (\n                            (\n                              (\n                                (\n                                  ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n                                    coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n                                      placeholder[Int](34)\n                                    ).toBigInt\n                                  )\n                                ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n                              ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n                                    val i47 = tuple45._2\n                                    val l48 = coll30(i47)\n                                    val bi49 = tuple45._1\n                                    if (l48 > placeholder[Long](40)) {(\n                                      val box50 = coll29(i47)\n                                      val bi51 = l48.toBigInt\n                                      val bi52 = box50.R4[Int].get.toBigInt\n                                      val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n                                      bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n                                    )} else { bi49 }\n                                  }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n                            ) && coll39.slice(placeholder[Int](45), i40).forall(\n                              {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n                            )\n                          ) && coll42.indices.forall({(i45: Int) =>\n                              val coll47 = coll29(i45).tokens\n                              (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n                            })\n                        ) && ((i43 == i44) && (i43 == coll42.size))\n                      ) && (i44 == coll41.size)\n                    ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n                  ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n                ) && (l7 == max(l8, placeholder[Long](52)))\n              ) && (l9 == max(l10, placeholder[Long](53)))\n            ) && (l11 == max(l12, placeholder[Long](54)))\n          ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n        ) && (l13 == max(l14, placeholder[Long](57)))\n      ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n    ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "16661a0a4fbe147b037b4099f09f839c587a38fee6fa8c5c4f12d05a5405268b",
          "index": 0,
          "amount": 1,
          "name": "Logic NFT ERG-2.0",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "110a80a0b787e90500003c8087a70e1000641e80b48913",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[100000000000,0,0,30,15000000,8,0,50,15,20000000]"
        },
        "R5": {
          "serializedValue": "1a022046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1207601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20",
          "sigmaType": "Coll[Coll[SByte]]",
          "renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1,7601494c813a7b1acbdecc042d9eb337ea79a556221c9567685f82077cea7b20]"
        },
        "R6": {
          "serializedValue": "1102f015f015",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[1400,1400]"
        }
      },
      "spentTransactionId": "d4d49e99a37a78c6e84eff5a537579ea9be59e65154ceec97316b9326b394e2a",
      "mainChain": true
    },
    {
      "boxId": "6af21343cac6df9589b12d671c516bc4a36073da7aab390356b68254fe7d6a4f",
      "transactionId": "389369c129060d98ba1d68c3795998eceb6abd041514d5725c549a839ddb5537",
      "blockId": "ae47956500e5a0ae50934f699ab6e2f1d0ad90488e156f705d1c73a8300c4369",
      "value": 1000000,
      "index": 10,
      "globalIndex": 53757674,
      "creationHeight": 1728249,
      "settlementHeight": 1728252,
      "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": "bcf1c1203e64333bd7d22f7a99db3fda62815955333bee2140d970d259a7713a",
      "mainChain": true
    }
  ],
  "size": 13679,
  "isUnconfirmed": false
}