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Transaction

9/2/2023 05:19:18 PM
ID: 131846da3f...9ab1
Inputs (12)
#0
f45513ba03ea...350e
Spent
Address:
Spectrum Finance (Yield Farm)
Output transaction:
b8bc54c208fa...3fee
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#1
ae50a8ebba0b...9a8f
Spent
Address:
9h9y3T3W84Ut...Cwxc
Output transaction:
b8bc54c208fa...3fee
Settlement height:
1,082,532
Value:
17.82 ERG
#2
2b49780da7e2...c435
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
59e561c0c3d6...80e6
Settlement height:
1,081,815
Value:
0.000522 ERG
Tokens:
Loading assets...
#3
d1eb3b94ffa7...385e
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
#4
1ce99bc9e257...69d3
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
#5
7826fa047a65...1610
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
#6
13cb229b9591...8ed7
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
#7
9761d17cd806...8890
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
#8
4d31bc60f37e...cbc5
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
#9
f15f8cad087b...1203
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
#10
167b936ba55a...ea5b
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
#11
01f14a360970...1c78
Spent
Address:
ynjTHNBGREHK...QD2P
Output transaction:
562cc9abb830...dfdb
Settlement height:
1,081,814
Value:
0.000522 ERG
Tokens:
Loading assets...
Outputs (23)
#0
ed5f3fb4f815...cfd8
Spent
Address:
Spectrum Finance (Yield Farm)
Spent in transaction:
73aa3c614fe1...0dda
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#1
009701482044...14c8
Spent
Address:
9h9y3T3W84Ut...Cwxc
Spent in transaction:
73aa3c614fe1...0dda
Settlement height:
1,082,532
Value:
17.81 ERG
#2
75087163e726...6073
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#3
24b34dde00ec...6eb7
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#4
61212918d714...0dff
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#5
cf9a188807f9...9fc0
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#6
11bcbd6483f0...9f7d
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#7
5a13501c4d23...200d
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#8
ef8893c47d21...2917
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#9
9b952e77efa8...17d4
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#10
1951cbb1ef04...7d99
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#11
c5b0f05851f4...defb
Spent
Address:
ynjTHNBGREHK...QD2P
Spent in transaction:
36b6a32a5a49...f234
Settlement height:
1,082,532
Value:
0.000522 ERG
Tokens:
Loading assets...
#12
ee7d16b5b3e4...ab91
Spent
Address:
9hVyFeAFDQoq...QTfo
Spent in transaction:
5a3a1292ea46...826a
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
0
#13
671cc33b1e70...6233
Spent
Address:
9fJjwGiL1EN9...31Q9
Spent in transaction:
4ef067281f24...aba4
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
0
#14
b3078f3e25a7...a5d2
Spent
Address:
9fJzKoTdK7Bb...XkzB
Spent in transaction:
90871fb2fb3a...81fa
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
4
#15
244d33a01514...660e
Spent
Address:
Baseless Bureau of Investigation (Giga Whale)
Spent in transaction:
29ef49e0799f...5da7
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
10.40
#16
2158b20d6ed4...b403
Spent
Address:
9ggp8PyhoKPv...GZPw
Spent in transaction:
c6f321ac8171...e489
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
0
#17
a5d182dc3391...dfc5
Spent
Address:
9fzkuEkMDeAT...QLGt
Spent in transaction:
f75132b0a4d9...50ea
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
0
#18
f173685cfed2...4b01
Spent
Address:
9gETFtAExM5p...hwU3
Spent in transaction:
3a478fe1532c...f4be
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
0
#19
f3a7b49d6392...492e
Spent
Address:
9ggp8PyhoKPv...GZPw
Spent in transaction:
c6f321ac8171...e489
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
0
#20
b29bc4441f3e...3956
Spent
Address:
9figafj76a2F...NGJM
Spent in transaction:
564c5e2dbac5...096a
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
1
#21
bf35d509845b...5de4
Spent
Address:
9fUGQkoGZpNa...sUqz
Spent in transaction:
2e51207484c7...48b0
Settlement height:
1,082,532
Value:
0.00025 ERG
Tokens:
SPF
1
#22
a52b7b120431...6a1a
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
1d29a913b8a3...f190
Settlement height:
1,082,532
Value:
0.003 ERG
Transaction Details
Status: Confirmed
Size: 10.95 KB
Received time: 9/2/2023 05:19:18 PM
Included in blocks: 1,082,532
Confirmations: 686,580
Total coins transferred: 17.83 ERG
Fees: 0.003 ERG
Fees per byte: 0.000000268 ERG
Raw Transaction Data
{
  "id": "131846da3f762d0be3b4043aae2256b679d03e3ed3e46220800f6f60c2839ab1",
  "blockId": "0f16b3762383ac53160f41bd246d586fe22a1578660ec059982818ba7123ddb5",
  "inclusionHeight": 1082532,
  "timestamp": 1693675158547,
  "index": 46,
  "globalIndex": 5768245,
  "numConfirmations": 686580,
  "inputs": [
    {
      "boxId": "f45513ba03ea23ba1aa8b20d0724959401bfb2733a4e277909c0f7fbc749350e",
      "value": 522000,
      "index": 0,
      "spendingProof": null,
      "outputBlockId": "0f16b3762383ac53160f41bd246d586fe22a1578660ec059982818ba7123ddb5",
      "outputTransactionId": "b8bc54c208fa3adb44c74a88701cd996a7f38bc226d734a9e432bab86c8b3fee",
      "outputIndex": 0,
      "outputGlobalIndex": 32300344,
      "outputCreatedAt": 1082530,
      "outputSettledAt": 1082532,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 1\n3: 1\n4: 2\n5: 2\n6: 3\n7: 3\n8: 4\n9: 4\n10: 2\n11: 1\n12: 0\n13: 0\n14: 1\n15: 1\n16: 0\n17: 5\n18: 0\n19: 0\n20: 2\n21: 1\n22: 1\n23: Coll(5,8,-13,98,61,75,43,-29,-67,-71,115,123,62,101,100,79,1,17,103,-18,-5,-125,13,-103,101,32,95,2,44,-19,-92,13)\n24: 0\n25: 1\n26: 0\n27: 1\n28: 1\n29: 3\n30: 0\n31: 0\n32: 9223372036854775807\n33: 0\n34: 0\n35: 1\n36: CBigInt(1)\n37: 0\n38: 0\n39: false",
      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.tokens\n  val tuple4 = coll3(placeholder[Int](1))\n  val coll5 = SELF.R4[Coll[Int]].get\n  val l6 = SELF.R5[Long].get\n  val l7 = SELF.R6[Long].get\n  val tuple8 = coll2(placeholder[Int](2))\n  val tuple9 = coll3(placeholder[Int](3))\n  val tuple10 = coll2(placeholder[Int](4))\n  val tuple11 = coll3(placeholder[Int](5))\n  val tuple12 = coll2(placeholder[Int](6))\n  val tuple13 = coll3(placeholder[Int](7))\n  val coll14 = tuple13._1\n  val tuple15 = coll2(placeholder[Int](8))\n  val tuple16 = coll3(placeholder[Int](9))\n  val coll17 = tuple16._1\n  val l18 = tuple11._2\n  val l19 = tuple10._2 - l18\n  val l20 = tuple9._2\n  val i21 = coll5(placeholder[Int](10))\n  val i22 = HEIGHT - i21 + placeholder[Int](11)\n  val i23 = coll5(placeholder[Int](12))\n  val i24 = i22 / i23\n  val i25 = if (i22 % i23 > placeholder[Int](13)) { i24 + placeholder[Int](14) } else { i24 }\n  val i26 = coll5(placeholder[Int](15))\n  val l27 = i26.toLong\n  val l28 = l6 / l27\n  val l29 = tuple12._2 - tuple13._2\n  val l30 = tuple16._2\n  val l31 = tuple15._2 - l30\n  sigmaProp(\n    (\n      (\n        (\n          (\n            (coll2(placeholder[Int](16)) == tuple4) && (\n              (((box1.R4[Coll[Int]].get == coll5) && (box1.R5[Long].get == l6)) && (box1.R6[Long].get == l7)) && (box1.creationInfo._1 >= SELF.creationInfo._1)\n            )\n          ) && (box1.propositionBytes == SELF.propositionBytes)\n        ) && ((((tuple8._1 == tuple9._1) && (tuple10._1 == tuple11._1)) && (tuple12._1 == coll14)) && (tuple15._1 == coll17))\n      ) && (coll2.size == placeholder[Int](17))\n    ) && if (l19 > placeholder[Long](18)) {(\n      val l32 = l19 * l27 - max(placeholder[Long](19), i25.toLong)\n      val box33 = OUTPUTS(placeholder[Int](20))\n      (\n        (\n          (l6 - l20.toBigInt + l7.toBigInt >= if (i25 <= i26) { i25 } else { i26 + placeholder[Int](21) } - placeholder[Int](22).toLong * l28.toBigInt) && (\n            l19 == !l29\n          )\n        ) && (l32 == !l31)\n      ) && (\n        (\n          (\n            ((blake2b256(box33.propositionBytes) == placeholder[Coll[Byte]](23)) && ((coll14, l19) == box33.tokens(placeholder[Int](24)))) && (\n              (coll17, l32) == box33.tokens(placeholder[Int](25))\n            )\n          ) && box33.R6[SigmaProp].isDefined\n        ) && (box33.R7[Coll[Byte]].get == tuple4._1)\n      )\n    )} else {\n      if (l19 < placeholder[Long](26)) {\n        (\n          (\n            (l6 - l20.toBigInt + l7.toBigInt >= if (i25 <= i26) { i25 } else { i26 + placeholder[Int](27) } - placeholder[Int](28).toLong * l28.toBigInt) || (\n              HEIGHT >= i21 + i26 * i23 + coll5(placeholder[Int](29))\n            )\n          ) && (l29 == !l19)\n        ) && (l31 >= if (i25 > i26) { placeholder[Long](30) } else { l29 * l27 - max(placeholder[Long](31), i25.toLong) })\n      } else {(\n        val i32 = box1.R7[Int].get\n        val i33 = i26 - i32\n        val l34 = i33.toLong\n        val l35 = placeholder[Long](32) - l30 - l18 * l34\n        if ((l35 > placeholder[Long](33)) && (l31 > placeholder[Long](34))) {\n          (\n            (\n              ((i32 <= i25 - placeholder[Int](35)) && (l20 - l34 * l28 <= l28 + l7)) && (\n                !tuple8._2 - l20.toBigInt <= l20.toBigInt - l6.toBigInt * i33.toBigInt / i26.toBigInt - placeholder[BigInt](36) * l31.toBigInt / l35.toBigInt\n              )\n            ) && (l19 == placeholder[Long](37))\n          ) && (l29 == placeholder[Long](38))\n        } else { placeholder[Boolean](39) }\n      )}\n    }\n  )\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "5f22cb20453e0856acb4b40e4ee2430e4b73a5abe4e72a0b2235a0adfb48a2be",
          "index": 0,
          "amount": 1,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "9a06d9e545a41fd51eeffc5e20d818073bf820c635e2a9d922269913e0de369d",
          "index": 1,
          "amount": 1258734789216,
          "name": "SPF",
          "decimals": 6,
          "type": "EIP-004"
        },
        {
          "tokenId": "c7e22029868ecba3d43c385bb42b8a1c96d0114ad5261ec7e0d27a6f24254f92",
          "index": 2,
          "amount": 33439151698559,
          "name": "Ergo_Spectrum Finance_LP",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "8c877434025cc85896ef2038d7ee40e0868bd3f2776c9f4a4e3d85bcaf512b10",
          "index": 3,
          "amount": 9223338597703077000,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "b970177c79ee09a9d31602c3fa97afa04ed7e64a1e3e09e6d4469039abd8303d",
          "index": 4,
          "amount": 9218321124253958000,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "1004a00be802a4cc8101a00b",
          "sigmaType": "Coll[SInt]",
          "renderedValue": "[720,180,1061650,720]"
        },
        "R5": {
          "serializedValue": "0580e0bcefa757",
          "sigmaType": "SLong",
          "renderedValue": "1500000000000"
        },
        "R6": {
          "serializedValue": "059003",
          "sigmaType": "SLong",
          "renderedValue": "200"
        },
        "R7": {
          "serializedValue": "043a",
          "sigmaType": "SInt",
          "renderedValue": "29"
        }
      }
    },
    {
      "boxId": "ae50a8ebba0b7df65b260f99ef597d53ad9c74c50433bbabc010c3c5f6df9a8f",
      "value": 17819456000,
      "index": 1,
      "spendingProof": "95cc8434b44bb0c13c9a8254d63a61923d11ce5842237671ffcaf9ce215ed660f05b9c77b84e9c98cc7860ab5eb401bddb827786f75bb027",
      "outputBlockId": "0f16b3762383ac53160f41bd246d586fe22a1578660ec059982818ba7123ddb5",
      "outputTransactionId": "b8bc54c208fa3adb44c74a88701cd996a7f38bc226d734a9e432bab86c8b3fee",
      "outputIndex": 1,
      "outputGlobalIndex": 32300345,
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      "assets": [
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          "sigmaType": "Coll[SByte]",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "assets": [
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "assets": [
        {
          "tokenId": "8c877434025cc85896ef2038d7ee40e0868bd3f2776c9f4a4e3d85bcaf512b10",
          "index": 0,
          "amount": 5171367543,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
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          "index": 1,
          "amount": 786047866536,
          "name": "",
          "decimals": 0,
          "type": "EIP-004"
        },
        {
          "tokenId": "2374c31e618add4b908f6045cee29a8365ac2159c8878e8089c41306eb81c2d2",
          "index": 2,
          "amount": 1,
          "name": "Spectrum YF staking bundle",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "0e1a537065637472756d205946207374616b696e672062756e646c65",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "537065637472756d205946207374616b696e672062756e646c65"
        },
        "R5": {
          "serializedValue": "0ea80154686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203566323263623230343533653038353661636234623430653465653234333065346237336135616265346537326130623232333561306164666234386132626529206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "54686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203566323263623230343533653038353661636234623430653465653234333065346237336135616265346537326130623232333561306164666234386132626529206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e"
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        "R6": {
          "serializedValue": "08cd029e15bb296e5b2a302554f24bf024a2ab8b3d5a9c15e7cdefd6ed2b713c747708",
          "sigmaType": "SSigmaProp",
          "renderedValue": "029e15bb296e5b2a302554f24bf024a2ab8b3d5a9c15e7cdefd6ed2b713c747708"
        },
        "R7": {
          "serializedValue": "0e205f22cb20453e0856acb4b40e4ee2430e4b73a5abe4e72a0b2235a0adfb48a2be",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "5f22cb20453e0856acb4b40e4ee2430e4b73a5abe4e72a0b2235a0adfb48a2be"
        }
      }
    },
    {
      "boxId": "01f14a360970071a68bfef9bb369081477efbb9f9655c40e874231625fe91c78",
      "value": 522000,
      "index": 11,
      "spendingProof": null,
      "outputBlockId": "82f399d85b88e3f96217b4600c67c654e0424e5a48b67bc67c9eafa1f07f00dd",
      "outputTransactionId": "562cc9abb830ef0ac62bef910d48460e7570241aa42cc981d1dea24f224adfdb",
      "outputIndex": 11,
      "outputGlobalIndex": 32267873,
      "outputCreatedAt": 1081812,
      "outputSettledAt": 1081814,
      "ergoTree": "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",
      "ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 2\n4: 0\n5: 1\n6: CBigInt(1)\n7: CBigInt(0)\n8: 0\n9: 0\n10: 1\n11: 2\n12: 1\n13: 9223372036854775807\n14: 4\n15: 0\n16: 1\n17: 1\n18: 2\n19: 1\n20: 1\n21: 0\n22: 0\n23: true\n24: false\n25: 0\n26: 2\n27: 0\n28: 3\n29: 2\n30: 1\n31: 9223372036854775806\n32: false",
      "ergoTreeScript": "{\n  val box1 = OUTPUTS(placeholder[Int](0))\n  val coll2 = box1.tokens\n  val coll3 = SELF.R7[Coll[Byte]].get\n  val box4 = INPUTS(placeholder[Int](1))\n  val coll5 = box4.tokens\n  val l6 = coll5(placeholder[Int](2))._2\n  val l7 = coll2(placeholder[Int](3))._2 - l6\n  val prop8 = SELF.R6[SigmaProp].get\n  val coll9 = SELF.tokens\n  val tuple10 = coll9(placeholder[Int](4))\n  val tuple11 = coll5(placeholder[Int](5))\n  val bi12 = placeholder[BigInt](6)\n  val bi13 = placeholder[BigInt](7)\n  sigmaProp((coll2(placeholder[Int](8))._1 == coll3) && if (l7 == placeholder[Long](9)) {(\n      val box14 = OUTPUTS(getVar[Int](0.toByte).get)\n      val box15 = OUTPUTS(getVar[Int](1.toByte).get)\n      val i16 = box4.R4[Coll[Int]].get(placeholder[Int](10))\n      val opt17 = box1.R8[Int]\n      val i18 = i16 - if (opt17.isDefined) { opt17.get } else { box1.R7[Int].get }\n      val coll19 = coll9(placeholder[Int](11))._1\n      val coll20 = box15.tokens\n      val tuple21 = coll9(placeholder[Int](12))\n      val l22 = tuple21._2\n      val l23 = i18.toLong\n      val l24 = l22 - l23 * tuple10._2\n      val bi25 = tuple11._2.toBigInt - box4.R5[Long].get.toBigInt * i18.toBigInt / i16.toBigInt - bi12 * l24.toBigInt / placeholder[Long](13) - coll5(placeholder[Int](14))._2 - l6 * l23.toBigInt\n      ((box14.propositionBytes == prop8.propBytes) && (((((box15.R6[SigmaProp].get == prop8) && (box15.R7[Coll[Byte]].get == coll3)) && (box15.propositionBytes == SELF.propositionBytes)) && if (i18 > placeholder[Int](15)) {(\n              val tuple26 = coll20(placeholder[Int](16))\n              (((coll19, placeholder[Long](17)) == coll20(placeholder[Int](18))) && (tuple26._1 == tuple21._1)) && (l22 - tuple26._2 == l24)\n            )} else { (coll19, placeholder[Long](19)) == coll20(placeholder[Int](20)) }) && (coll20(placeholder[Int](21)) == tuple10))) && if (bi25 > bi13) {(\n        val tuple26 = box14.tokens(placeholder[Int](22))\n        (tuple26._1 == tuple11._1) && (tuple26._2.toBigInt >= bi25 - bi12)\n      )} else { if (bi25 == bi13) { placeholder[Boolean](23) } else { placeholder[Boolean](24) } }\n    )} else { if (l7 < placeholder[Long](25)) { INPUTS(placeholder[Int](26)).tokens(placeholder[Int](27)) == (if (coll9.size == placeholder[Int](28)) { coll9(placeholder[Int](29))._1 } else { coll9(placeholder[Int](30))._1 }, placeholder[Long](31)) } else { placeholder[Boolean](32) } })\n}",
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      "assets": [
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          "decimals": 0,
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        {
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        },
        {
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          "name": "Spectrum YF staking bundle",
          "decimals": 0,
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      ],
      "additionalRegisters": {
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          "sigmaType": "Coll[SByte]",
          "renderedValue": "537065637472756d205946207374616b696e672062756e646c65"
        },
        "R5": {
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          "renderedValue": "54686520726570726573656e746174696f6e206f6620796f757220736861726520696e20746865207969656c64206661726d696e6720706f6f6c2028706f6f6c2069643a203566323263623230343533653038353661636234623430653465653234333065346237336135616265346537326130623232333561306164666234386132626529206f6e2074686520537065637472756d2046696e616e636520706c6174666f726d2e"
        },
        "R6": {
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          "sigmaType": "SSigmaProp",
          "renderedValue": "027d599415ab9a54aef414cd8682e1c8f24e1156770d8fd289c5b5a45d34174632"
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        "R7": {
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        }
      }
    }
  ],
  "dataInputs": [],
  "outputs": [
    {
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      "transactionId": "131846da3f762d0be3b4043aae2256b679d03e3ed3e46220800f6f60c2839ab1",
      "blockId": "0f16b3762383ac53160f41bd246d586fe22a1578660ec059982818ba7123ddb5",
      "value": 522000,
      "index": 0,
      "globalIndex": 32300367,
      "creationHeight": 1082530,
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      "globalIndex": 32300388,
      "creationHeight": 1082530,
      "settlementHeight": 1082532,
      "ergoTree": "0008cd027d599415ab9a54aef414cd8682e1c8f24e1156770d8fd289c5b5a45d34174632",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(7d5994,b76648,...)))}",
      "address": "9fUGQkoGZpNaVYdCvWZmzcK9hqpN8duYGyGjLwmCFTBxmiRsUqz",
      "assets": [
        {
          "tokenId": "9a06d9e545a41fd51eeffc5e20d818073bf820c635e2a9d922269913e0de369d",
          "index": 0,
          "amount": 1467120,
          "name": "SPF",
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          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "2e51207484c72417192e29d9a35a7d9180e1e9a3e06d00b2727cae82568948b0",
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    },
    {
      "boxId": "a52b7b12043141e183222d5e378e772c7ad3d8773f0e8e90deafb60da71f6a1a",
      "transactionId": "131846da3f762d0be3b4043aae2256b679d03e3ed3e46220800f6f60c2839ab1",
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      "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)}",
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      "additionalRegisters": {},
      "spentTransactionId": "1d29a913b8a300e2b40f6025c18569008fdfd80bf77f974fb36a55979680f190",
      "mainChain": true
    }
  ],
  "size": 11213,
  "isUnconfirmed": false
}