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Transaction

6/13/2022 08:28:08 AM
ID: 32739781ff...e9da
Inputs (2)
#0
5e5ba9185622...1e75
Spent
Address:
Vek63kH3dkZ6...d8oe
Output transaction:
82ef8bbcf110...dde4
Settlement height:
770,867
Value:
0.001 ERG
Tokens:
Loading assets...
#1
0b984442ae80...b15b
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
5cfb59a63fb9...8af1
Settlement height:
770,975
Value:
63.01 ERG
Outputs (23)
#0
036c72199370...5657
Spent
Address:
Vek63kH3dkZ6...d8oe
Spent in transaction:
537b6d5cb521...b01e
Settlement height:
770,975
Value:
0.001 ERG
Tokens:
Loading assets...
#1
42e83763f164...96ac
Spent
Address:
9gdLf3Zg1QHg...V29T
Spent in transaction:
9badecb8a56d...fabb
Settlement height:
770,975
Value:
60.93 ERG
#2
b98e6c5b80c0...b260
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
5e05374cd62b...d122
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
950.95
#3
35b9c031cafe...b70b
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
a0a96567a51e...b535
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
626.05
#4
7312a1f124ad...b596
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
081325f6f631...2f62
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
2,065.05
#5
ccc6172882bf...34de
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
8f23bae660ef...2c0e
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
482.76
#6
157f27357e4d...6c0b
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
4130369a617d...d453
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
721.11
#7
4eb0f4a87853...9098
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
d9c6bd564c75...759e
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
189.02
#8
01061e6b0cfd...c5e7
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
7ecbad2de08c...7768
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
649.02
#9
d02a71a524fe...ea7c
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
6dbfb5b9ef3b...ff76
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
404.64
#10
61e713441007...13e9
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
438248290d50...0b84
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
384.65
#11
0ee359f25709...8926
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
fcd7f6e5caa4...c48e
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
1,002.21
#12
e489c66dbd05...ffd0
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
e6f85cabf760...4828
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
329.95
#13
cc455988aa70...6d46
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
7e8ca6bf2427...bd5f
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
1,830.80
#14
1e68e44b015a...7a18
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
e6206976ee81...5c5f
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
385.96
#15
27541c9dd90d...f624
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
285db0847179...8f5f
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
416.97
#16
b8e5f944a6f1...c792
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
3167cb03192f...e160
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
823.38
#17
5eefe9f36e63...8c34
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
b0bc7a68f56f...1e3f
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
584.52
#18
8b3ef60864c3...7b71
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
3c15153fc101...5eee
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
627.22
#19
c2b0da0f956a...506f
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
106e758a69a9...f41c
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
891.06
#20
063af7ae3b0c...71d9
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
734366043118...97bc
Settlement height:
770,975
Value:
0.01 ERG
Tokens:
NETA
454.22
#21
c44b846346ca...8587
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
dbe70e9f3830...1e59
Settlement height:
770,975
Value:
0.428333333 ERG
#22
7af2c14413f8...cd04
Spent
Address:
9fMLVMsG8U1P...fc3Q
Spent in transaction:
07a17126226e...c48e
Settlement height:
770,975
Value:
1.46 ERG
Tokens:
NETA
0
Transaction Details
Status: Confirmed
Size: 21.2 KB
Received time: 6/13/2022 08:28:08 AM
Included in blocks: 770,975
Confirmations: 985,833
Total coins transferred: 63.01 ERG
Fees: 0.428333333 ERG
Fees per byte: 0.000019732 ERG
Raw Transaction Data
{
  "id": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
  "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
  "inclusionHeight": 770975,
  "timestamp": 1655108888819,
  "index": 2,
  "globalIndex": 3350877,
  "numConfirmations": 985833,
  "inputs": [
    {
      "boxId": "5e5ba91856224dc34a0348b4f4e831e7cad2e573b33eb00120a5f5f3b0051e75",
      "value": 1000000,
      "index": 0,
      "spendingProof": "445bc67bb81fbef6bcd8aae6d95a7ed3e84829c791b1e6b5d081f4b5a285435f26229524e63d9c3da1826b2b78c4074f8b510d53d008c995",
      "outputBlockId": "a1c7e6dde4b857830f8891465d81a82b71596f16110b7f230fb9797c9a4c10c9",
      "outputTransactionId": "82ef8bbcf110b551da60d8d028015402f369a1d2819abb412a8b80d4c81adde4",
      "outputIndex": 0,
      "outputGlobalIndex": 17825701,
      "outputCreatedAt": 770864,
      "outputSettledAt": 770867,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(71,44,61,78,-54,-96,-113,-73,57,47,-16,65,-18,46,106,-9,95,74,85,-120,16,-89,75,40,96,5,73,-43,57,40,16,-24)\n2: 2\n3: 0\n4: 1\n5: 100\n6: 2\n7: -2\n8: 1\n9: Coll(-60,30,-111,54,-57,63,-78,-18,56,-102,-88,68,14,-61,-38,66,28,-22,61,41,88,-114,-117,-113,36,-51,-80,-66,89,32,-40,25)\n10: 100000\n11: 10000000\n12: 100000\n13: 100000\n14: 1\n15: 10000\n16: 1000\n17: 100000\n18: 100000\n19: 100000\n20: Coll(125,46,40,67,16,99,-53,-79,-23,-31,68,104,-6,-52,71,-71,-124,-39,98,83,44,25,-80,-79,79,116,-48,-50,-98,-44,89,-66)\n21: 0\n22: 0\n23: 0\n24: 1\n25: 3000\n26: 0\n27: 0\n28: 0\n29: 10000000\n30: SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))\n31: SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))",
      "ergoTreeScript": "{\n  val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = placeholder[Coll[Byte]](1)\n  val tuple4 = coll2(placeholder[Int](2))\n  val box5 = OUTPUTS(placeholder[Int](3))\n  val coll6 = box5.tokens\n  val coll7 = SELF.tokens\n  val tuple8 = coll6(placeholder[Int](4))\n  val func9 = {(tuple9: (Long, Long)) =>\n    val l11 = tuple9._2\n    val l12 = tuple9._1 - l11 * placeholder[Long](5) / l11\n    (l12 < placeholder[Long](6)) && (l12 > placeholder[Long](7))\n  }\n  val l10 = INPUTS(placeholder[Int](8)).value\n  val coll11 = OUTPUTS.filter({(box11: Box) => blake2b256(box11.propositionBytes) == placeholder[Coll[Byte]](9) })\n  val l12 = l10 - l10 * SELF.R5[Long].get / placeholder[Long](10) - coll11.size.toLong * placeholder[Long](11)\n  val l13 = l12 * box1.R4[Int].get.toLong\n  val l14 = box1.value\n  val l15 = tuple4._2 / placeholder[Long](12) * l13 / placeholder[Long](13) / l14 + l14 * placeholder[Int](14).toLong / placeholder[Long](15) * placeholder[\n    Long\n  ](16) + l13 / placeholder[Long](17) * placeholder[Long](18)\n  val l16 = SELF.R4[Long].get\n  val l17 = l15 + l15 * l16 / placeholder[Long](19)\n  val l18 = box5.R5[Long].get\n  sigmaProp(\n    (\n      (\n        allOf(Coll[Boolean](placeholder[Coll[Byte]](20) == coll2(placeholder[Int](21))._1, coll3 == tuple4._1)) && allOf(\n          Coll[Boolean](\n            box5.propositionBytes == SELF.propositionBytes, coll6(placeholder[Int](22))._1 == coll7(placeholder[Int](23))._1, tuple8._1 == coll3, func9(\n              (tuple8._2, coll7(placeholder[Int](24))._2 - l17)\n            ), box5.value == SELF.value, box5.R4[Long].get == l16, l18 <= placeholder[Long](25), l18 >= placeholder[Long](26)\n          )\n        )\n      ) && allOf(\n        Coll[Boolean](\n          func9((coll11.fold(placeholder[Long](27), {(tuple19: (Long, Box)) => tuple19._1 + tuple19._2.tokens(placeholder[Int](28))._2 }), l17)), coll11.forall(\n            {(box19: Box) => box19.value == placeholder[Long](29) }\n          )\n        )\n      )\n    ) && OUTPUTS.exists({(box19: Box) => func9((box19.value, l12)) && (box19.propositionBytes == placeholder[SigmaProp](30).propBytes) })\n  ) && placeholder[SigmaProp](31)\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "01e0ae6997711e9fa0422287a82a8815f64f805c2735aec49fe2bb90ef5fbc78",
          "index": 0,
          "amount": 1,
          "name": "NETA Emission Box NFT",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 1,
          "amount": 9907277560000,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "05e0d702",
          "sigmaType": "SLong",
          "renderedValue": "22000"
        },
        "R5": {
          "serializedValue": "05f02e",
          "sigmaType": "SLong",
          "renderedValue": "3000"
        }
      }
    },
    {
      "boxId": "0b984442ae809e4aa74b740c764b12282a166f2ef690c359870dac4a4760b15b",
      "value": 63009100000,
      "index": 1,
      "spendingProof": "4394aad52f86c77ded8f630a382c8cf3d355c0f2382c8b691f8b501719035546e8192e105ca820309931019153e64ec7276e81c8e7f7189c",
      "outputBlockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "outputTransactionId": "5cfb59a63fb9c8815cdbb29b82769dbcecabab6d6040a37af8887e487e318af1",
      "outputIndex": 0,
      "outputGlobalIndex": 17831227,
      "outputCreatedAt": 770972,
      "outputSettledAt": 770975,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [
    {
      "boxId": "4ec5f0bb7df3afbe626d241a2d246b50b9897176eefbaf31689591e7e078cb71",
      "value": 48239613492314,
      "index": 0,
      "outputBlockId": "14312ff396b9880182eb47ef28c310daebc12959c2ddb8356ce79d97a09c2688",
      "outputTransactionId": "09d25f0dda7e4082ba6abc2f6a39050af4a8434c66871586dc9499e55c96b847",
      "outputIndex": 0,
      "ergoTree": "1999030f0400040204020404040405feffffffffffffffff0105feffffffffffffffff01050004d00f040004000406050005000580dac409d819d601b2a5730000d602e4c6a70404d603db63087201d604db6308a7d605b27203730100d606b27204730200d607b27203730300d608b27204730400d6099973058c720602d60a999973068c7205027209d60bc17201d60cc1a7d60d99720b720cd60e91720d7307d60f8c720802d6107e720f06d6117e720d06d612998c720702720fd6137e720c06d6147308d6157e721206d6167e720a06d6177e720906d6189c72117217d6199c72157217d1ededededededed93c27201c2a793e4c672010404720293b27203730900b27204730a00938c7205018c720601938c7207018c72080193b17203730b9593720a730c95720e929c9c721072117e7202069c7ef07212069a9c72137e7214067e9c720d7e72020506929c9c721372157e7202069c7ef0720d069a9c72107e7214067e9c72127e7202050695ed720e917212730d907216a19d721872139d72197210ed9272189c721672139272199c7216721091720b730e",
      "address": "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",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "04c80f",
          "sigmaType": "SInt",
          "renderedValue": "996"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "036c7219937036bdf4bac4fd6a648d692035a1cf5eb0d31ffd6e025610985657",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 1000000,
      "index": 0,
      "globalIndex": 17831231,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: Coll(71,44,61,78,-54,-96,-113,-73,57,47,-16,65,-18,46,106,-9,95,74,85,-120,16,-89,75,40,96,5,73,-43,57,40,16,-24)\n2: 2\n3: 0\n4: 1\n5: 100\n6: 2\n7: -2\n8: 1\n9: Coll(-60,30,-111,54,-57,63,-78,-18,56,-102,-88,68,14,-61,-38,66,28,-22,61,41,88,-114,-117,-113,36,-51,-80,-66,89,32,-40,25)\n10: 100000\n11: 10000000\n12: 100000\n13: 100000\n14: 1\n15: 10000\n16: 1000\n17: 100000\n18: 100000\n19: 100000\n20: Coll(125,46,40,67,16,99,-53,-79,-23,-31,68,104,-6,-52,71,-71,-124,-39,98,83,44,25,-80,-79,79,116,-48,-50,-98,-44,89,-66)\n21: 0\n22: 0\n23: 0\n24: 1\n25: 3000\n26: 0\n27: 0\n28: 0\n29: 10000000\n30: SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))\n31: SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))",
      "ergoTreeScript": "{\n  val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = placeholder[Coll[Byte]](1)\n  val tuple4 = coll2(placeholder[Int](2))\n  val box5 = OUTPUTS(placeholder[Int](3))\n  val coll6 = box5.tokens\n  val coll7 = SELF.tokens\n  val tuple8 = coll6(placeholder[Int](4))\n  val func9 = {(tuple9: (Long, Long)) =>\n    val l11 = tuple9._2\n    val l12 = tuple9._1 - l11 * placeholder[Long](5) / l11\n    (l12 < placeholder[Long](6)) && (l12 > placeholder[Long](7))\n  }\n  val l10 = INPUTS(placeholder[Int](8)).value\n  val coll11 = OUTPUTS.filter({(box11: Box) => blake2b256(box11.propositionBytes) == placeholder[Coll[Byte]](9) })\n  val l12 = l10 - l10 * SELF.R5[Long].get / placeholder[Long](10) - coll11.size.toLong * placeholder[Long](11)\n  val l13 = l12 * box1.R4[Int].get.toLong\n  val l14 = box1.value\n  val l15 = tuple4._2 / placeholder[Long](12) * l13 / placeholder[Long](13) / l14 + l14 * placeholder[Int](14).toLong / placeholder[Long](15) * placeholder[\n    Long\n  ](16) + l13 / placeholder[Long](17) * placeholder[Long](18)\n  val l16 = SELF.R4[Long].get\n  val l17 = l15 + l15 * l16 / placeholder[Long](19)\n  val l18 = box5.R5[Long].get\n  sigmaProp(\n    (\n      (\n        allOf(Coll[Boolean](placeholder[Coll[Byte]](20) == coll2(placeholder[Int](21))._1, coll3 == tuple4._1)) && allOf(\n          Coll[Boolean](\n            box5.propositionBytes == SELF.propositionBytes, coll6(placeholder[Int](22))._1 == coll7(placeholder[Int](23))._1, tuple8._1 == coll3, func9(\n              (tuple8._2, coll7(placeholder[Int](24))._2 - l17)\n            ), box5.value == SELF.value, box5.R4[Long].get == l16, l18 <= placeholder[Long](25), l18 >= placeholder[Long](26)\n          )\n        )\n      ) && allOf(\n        Coll[Boolean](\n          func9((coll11.fold(placeholder[Long](27), {(tuple19: (Long, Box)) => tuple19._1 + tuple19._2.tokens(placeholder[Int](28))._2 }), l17)), coll11.forall(\n            {(box19: Box) => box19.value == placeholder[Long](29) }\n          )\n        )\n      )\n    ) && OUTPUTS.exists({(box19: Box) => func9((box19.value, l12)) && (box19.propositionBytes == placeholder[SigmaProp](30).propBytes) })\n  ) && placeholder[SigmaProp](31)\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "01e0ae6997711e9fa0422287a82a8815f64f805c2735aec49fe2bb90ef5fbc78",
          "index": 0,
          "amount": 1,
          "name": "NETA Emission Box NFT",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 1,
          "amount": 9893458010000,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "05e0d702",
          "sigmaType": "SLong",
          "renderedValue": "22000"
        },
        "R5": {
          "serializedValue": "05f02e",
          "sigmaType": "SLong",
          "renderedValue": "3000"
        }
      },
      "spentTransactionId": "537b6d5cb5210a9f72b53fd440b4ee828c97835c48edc7a445fca904e102b01e",
      "mainChain": true
    },
    {
      "boxId": "42e83763f1648997a1b97781b978edc368e681e951514b05178a3b774a9796ac",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 60928827000,
      "index": 1,
      "globalIndex": 17831232,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "0008cd0315a5d99a010bf189b1abae2d9f21be6f3438803aca1e6aac739fbee31150d627",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))}",
      "address": "9gdLf3Zg1QHgH3BYjFrMA2DSm19CqPNKi9vTCeCT5NSmNZfV29T",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "9badecb8a56d044941c7f92486845776162fc2b90c0a49d50e93f6b1f4bffabb",
      "mainChain": true
    },
    {
      "boxId": "b98e6c5b80c006313413ff24f4eae8404689b4ca0d7a2c3130c592219c8ab260",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 2,
      "globalIndex": 17831233,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 950950739,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "5e05374cd62b43ad121e52df91f3c28da7d92b350a820930b5f184c5f054d122",
      "mainChain": true
    },
    {
      "boxId": "35b9c031cafe7def61d60e3e527169732797b4911157be3192a59d97bb76b70b",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 3,
      "globalIndex": 17831234,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 626047095,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "a0a96567a51e74eb5b16ddf5b5117cd5b0be733f181036a30d6d98b0f5f6b535",
      "mainChain": true
    },
    {
      "boxId": "7312a1f124ad231683b5f37709223549781eb3f381b6e9182433b5fdab73b596",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 4,
      "globalIndex": 17831235,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 2065052823,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "081325f6f6317e2fb2d4530d4ac7542bb8d78b0b36c73ab414a6bca87b522f62",
      "mainChain": true
    },
    {
      "boxId": "ccc6172882bfff3372252be700c60216557ff5c1ecd090a4fa5b7105b0f734de",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 5,
      "globalIndex": 17831236,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 482762812,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "8f23bae660ef77d834a2adc4d3753ae192119031a6a7963c6c0c7d5f96462c0e",
      "mainChain": true
    },
    {
      "boxId": "157f27357e4d882815cbaa9b2b66e15b696a65aa3e2e3127df645d0b6bf26c0b",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 6,
      "globalIndex": 17831237,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 721114424,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "4130369a617d648bea0a85647132c36250da5216ad1191b51d73518cdeb2d453",
      "mainChain": true
    },
    {
      "boxId": "4eb0f4a878535ed7bb80394cdfc2e6af9a9f786757fdd579afc45c0b8a5c9098",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 7,
      "globalIndex": 17831238,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 189016010,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "d9c6bd564c755445354b0b7e7fc2b89929fbdc1ea8bc1ca7d2a336ff4f85759e",
      "mainChain": true
    },
    {
      "boxId": "01061e6b0cfd23e8fd059c6a2af1da50cd99c6c504ac708403da59ad2891c5e7",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 8,
      "globalIndex": 17831239,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 649019215,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "7ecbad2de08cce0e725a2c78ec5219a0783806d1f5f37363884af39b40c87768",
      "mainChain": true
    },
    {
      "boxId": "d02a71a524fed8177c58257636d822eed7742ef5fa3cad807132f9d31975ea7c",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 9,
      "globalIndex": 17831240,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 404640483,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "6dbfb5b9ef3b3ade1de0ed4295f830851de9cdee3d21b88896ea24a9562aff76",
      "mainChain": true
    },
    {
      "boxId": "61e713441007319aa5ecaabcf48fc705aafd926032b0fb363b830917936113e9",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 10,
      "globalIndex": 17831241,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 384652407,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "438248290d50c052446ba6d3f6acee74c6be718a7066c0db235b1d6dfafc0b84",
      "mainChain": true
    },
    {
      "boxId": "0ee359f257092b048f9adfbfcd398cfdf7d09c7450c1b549dd9345bbaa928926",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 11,
      "globalIndex": 17831242,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 1002213720,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "fcd7f6e5caa4aa8d2dfdd9a0440bc590838384695f275d674f04748538b7c48e",
      "mainChain": true
    },
    {
      "boxId": "e489c66dbd05ea7f7160fd006824f51555f3cc3c2492cb4ab60f39933a2affd0",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 12,
      "globalIndex": 17831243,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 329950839,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "e6f85cabf760a7f9d4290d0e8b78d3ceab81a6e6f93a2e6ff75223fe95124828",
      "mainChain": true
    },
    {
      "boxId": "cc455988aa708be54001cab60317fcade374aad7df6fb60519725c5a7d206d46",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 13,
      "globalIndex": 17831244,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 1830803902,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "7e8ca6bf2427e2171a20ad5a67839d2a8f6cbf7ea5e14b24cd730d8ff364bd5f",
      "mainChain": true
    },
    {
      "boxId": "1e68e44b015a67f712dc7eb14819c09b178587a1b13ff663db62e3d978fd7a18",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 14,
      "globalIndex": 17831245,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 385957004,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "e6206976ee81ee065c9cbb296f6c06f2c05c159fc84db776b9a63acf29ca5c5f",
      "mainChain": true
    },
    {
      "boxId": "27541c9dd90d7aed02f6f305716a7eb4a657b55d40fbf960c09c6608f578f624",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 15,
      "globalIndex": 17831246,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 416969219,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "285db0847179f17fd891af7f2ac793be3b4f8b94731571267df2caec41b28f5f",
      "mainChain": true
    },
    {
      "boxId": "b8e5f944a6f1609a478b609eb36e4eaceb363d173dac757fb73238d293f4c792",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 16,
      "globalIndex": 17831247,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 823377697,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "3167cb03192fd95b07aa7ef95de2295ae98a8fe4742bf8c5bb881430f613e160",
      "mainChain": true
    },
    {
      "boxId": "5eefe9f36e632012febe431aa937ce0e1d1fc9866a3ff89811e7ec6318558c34",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 17,
      "globalIndex": 17831248,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 584518413,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "b0bc7a68f56f0d6b96afc1ffee7225b2dadefc3cd8f09a1ebf639efed9f61e3f",
      "mainChain": true
    },
    {
      "boxId": "8b3ef60864c30d1d49b80dd5c06eba54ffd086832c04b5ef40beca5011587b71",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 18,
      "globalIndex": 17831249,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 627218871,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "3c15153fc1016ee6f10f0f080c4b401c95b0881cba62be1516068b526db35eee",
      "mainChain": true
    },
    {
      "boxId": "c2b0da0f956a1e8fcb90e033b5bc4d1727060b7c839df9bfd469d689c173506f",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 19,
      "globalIndex": 17831250,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 891060299,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "106e758a69a9801ce2485edc16fd0d4487677477e0c00c0b4a4d972b1b59f41c",
      "mainChain": true
    },
    {
      "boxId": "063af7ae3b0c25f2eeb3ff88bbeaad5f9ddb17eb6d34e265bd0049b95dcd71d9",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 10000000,
      "index": 20,
      "globalIndex": 17831251,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
      "ergoTreeScript": "{\n  val box1 = INPUTS(placeholder[Int](0))\n  val coll2 = SELF.propositionBytes\n  val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n  val l4 = placeholder[Long](1)\n  val func5 = {(tuple5: (Long, Long)) =>\n    val l7 = tuple5._1\n    val l8 = tuple5._2\n    val bool9 = l8 != placeholder[Long](2)\n    val l10 = l8\n    val l11 = if (bool9) { l10 } else { l4 }\n    val l12 = l7 - l11\n    val l13 = l12 * placeholder[Long](3)\n    val l14 = l13 / l11\n    val bool15 = l14 < placeholder[Long](4)\n    val bool16 = \n      val bool16 = l14 > placeholder[Long](5)\n      bool16\n    \n    val bool17 = bool15 && bool16\n    bool17\n  }\n  val func6 = {(tuple6: (Long, Long)) =>\n    val l8 = tuple6._2\n    val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n    val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n    (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n  }\n  sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n      val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n      val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n          val coll11 = tuple9._2\n          coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n        }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n      val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n      val coll11 = SELF.tokens(placeholder[Int](21))._1\n      val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n      val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n      val l14 = l4\n      val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n      val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n          val coll18 = tuple16._2\n          coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n        }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n      ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n              val coll19 = tuple17._1\n              val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n              val coll21 = tuple17._2\n              val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n              val l23 = coll21(placeholder[Int](33))\n              val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n              val l25 = coll21(placeholder[Int](35))\n              if (i20 != placeholder[Int](36)) {(\n                val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n                if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n                    val func27 = func5\n                    func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n                  )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n              )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n            }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n              val l19 = tuple17._2\n              if (l19 > placeholder[Long](46)) {(\n                val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n                if (i20 != placeholder[Int](48)) {(\n                  val box21 = coll12(i20)\n                  func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n                )} else { placeholder[Boolean](51) }\n              )} else { placeholder[Boolean](52) }\n            })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n    )} else { placeholder[Boolean](57) })\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 454224018,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "734366043118d8d16b2707fb5c73e60a7d18182e2b12d3d3190406c1992b97bc",
      "mainChain": true
    },
    {
      "boxId": "c44b846346ca397ae1712bf3edfc82e33d02954b28389f097b9eb963de248587",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 428333333,
      "index": 21,
      "globalIndex": 17831252,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "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": "dbe70e9f383043c8f61926753c2ef0156d364d01ad57827f40197098bf8f1e59",
      "mainChain": true
    },
    {
      "boxId": "7af2c14413f86c238b2d24f6f0c22d73d279ad748158452846cde838e8e6cd04",
      "transactionId": "32739781ffbf48d803825290ba51df2f9db467d4611da2ee8e55dc8fc79ce9da",
      "blockId": "124770f0f51ba5bf1550021de0fd71d4f4305c9618c6cedd5e462d5fcd771f96",
      "value": 1461939667,
      "index": 22,
      "globalIndex": 17831253,
      "creationHeight": 770972,
      "settlementHeight": 770975,
      "ergoTree": "0008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed372027",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6d9d81,e53882,...)))}",
      "address": "9fMLVMsG8U1PHqHZ8JDQ4Yn6q5wPdruVn2ctwqaqCXVLfWxfc3Q",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 10,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "07a17126226efb8e26929d19c8d097a37519070356c677c39836eed648acc48e",
      "mainChain": true
    }
  ],
  "size": 21707,
  "isUnconfirmed": false
}