Transaction
ID: 1d0611079e...5617
Inputs (4)
Spent
Output transaction:
Settlement height:
Value:
1.33 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00020844 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
100,000
Spent
Address:
Output transaction:
Settlement height:
Value:
10,079.51 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Spent in transaction:
Settlement height:
Value:
1.3 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
10,079.5 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0072 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.026247018 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 442,322
Total coins transferred: 10,080.84 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000308 ERG
Raw Transaction Data
{
"id": "1d0611079eaf9edfc66b733a3cd2521dd71e8b5b24332e95e84f264ef5295617",
"blockId": "e5e70e3aaeef26b0a317d915058ab4e7ca8af7597a1b5ee205335f727e7211b5",
"inclusionHeight": 1325641,
"timestamp": 1723120041942,
"index": 2,
"globalIndex": 7620908,
"numConfirmations": 442322,
"inputs": [
{
"boxId": "7aad1ed48b5c2b27c66ce1f853768f813f11609e28d4c86f54e334af4387efac",
"value": 1326147018,
"index": 0,
"spendingProof": "89510766ee6e66d964fce9fa56f6625a281c9e1a75d23a9ecd7517abf3bb70a2699eb13fa4dc8208333cc9862bf90e9bc38463de66b71144",
"outputBlockId": "bdaa424d193d1860f7ae29860cc925ca2e0286756c41eb9a108b8b1765a7da4e",
"outputTransactionId": "62c787b844c01dbdb2a445b9bbe9ebd71d82e0d66366a8d04f49efb0ffd17ed1",
"outputIndex": 1,
"outputGlobalIndex": 42024379,
"outputCreatedAt": 1325634,
"outputSettledAt": 1325636,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: CBigInt(1)\n2: 0\n3: 1\n4: 0\n5: 100000000\n6: 100000000\n7: 2\n8: 1\n9: 0\n10: 100000000\n11: 100000000\n12: 100000000\n13: Coll(53,-42,-8,-125,-68,-101,9,-50,-55,93,-29,-117,-61,-73,-59,-48,29,81,-101,-120,-83,53,18,-69,-90,100,62,-75,-63,9,7,-128)\n14: 0\n15: 0\n16: Coll(-44,91,-64,7,122,-49,102,-74,14,89,-46,77,24,30,41,87,9,85,-56,48,57,-98,-34,36,77,89,-43,-1,114,106,-47,-114)\n17: 0\n18: Coll(3,-6,-14,-53,50,-97,46,-112,-42,-46,59,88,-39,27,-69,108,4,106,-95,67,38,28,-62,31,82,-5,-30,-126,75,-4,-65,4)\n19: 0\n20: 3\n21: 5000000\n22: 1000\n23: 2\n24: 2\n25: CBigInt(100)\n26: 3000000\n27: 1000000\n28: 0\n29: 0\n30: 1\n31: 0\n32: 1000000\n33: 1\n34: Coll(26,-82,111,-75,-122,125,-117,70,-90,-78,-2,-34,-122,-3,79,-75,-116,-100,-74,48,-124,30,35,-37,11,-95,-61,-46,-95,69,-57,88)\n35: 1000000\n36: 1000000\n37: 1\n38: 0\n39: 3\n40: 5000000\n41: 1000\n42: 2\n43: 2\n44: CBigInt(100)\n45: 2\n46: 0\n47: 0\n48: false\n49: 1\n50: 3\n51: 0\n52: 3\n53: 5000000\n54: 1000\n55: 2\n56: 2\n57: CBigInt(100)\n58: 3000000\n59: 1000000\n60: 0\n61: 100000000\n62: 5\n63: 100000000\n64: false\n65: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val ge2 = SELF.R8[GroupElement].get\n val coll3 = SELF.propositionBytes\n val coll4 = CONTEXT.dataInputs\n val tuple5 = SELF.R6[(Long, Long)].get\n val l6 = tuple5._1\n val bi7 = placeholder[BigInt](1)\n val coll8 = SELF.tokens\n val tuple9 = coll8(placeholder[Int](2))\n val l10 = tuple9._2\n val bi11 = l10.toBigInt\n val box12 = coll4(placeholder[Int](3))\n val coll13 = box12.R4[Coll[Long]].get\n val i14 = coll13.size\n val tuple15 = SELF.R5[(Int, Int)].get\n val i16 = tuple15._1\n val box17 = coll4(placeholder[Int](4))\n val coll18 = box17.R4[Coll[Long]].get\n val l19 = coll18.slice(tuple15._2, coll18.size).fold(placeholder[Long](5), {(tuple19: (Long, Long)) => tuple19._1 * tuple19._2 / placeholder[Long](6) })\n val box20 = coll4(placeholder[Int](7))\n val coll21 = box20.R4[Coll[Long]].get\n val bi22 = if (i14 == i16) { l19 } else {(\n val i22 = i16 + placeholder[Int](8)\n val l23 = coll21.slice(placeholder[Int](9), coll21.size).fold(l19, {(tuple23: (Long, Long)) => tuple23._1 * tuple23._2 / placeholder[Long](10) })\n if (i14 == i22) { l23 } else { coll13.slice(i22, i14).fold(l23, {(tuple24: (Long, Long)) => tuple24._1 * tuple24._2 / placeholder[Long](11) }) }\n )}.toBigInt\n val l23 = placeholder[Long](12)\n val bi24 = bi7 + bi11 * bi22 / l23.toBigInt\n val coll25 = SELF.R4[Coll[Byte]].get\n val coll26 = SELF.R7[Coll[Byte]].get\n val tuple27 = SELF.R9[(Long, Long)].get\n val l28 = tuple27._1\n val l29 = tuple27._2\n val coll30 = placeholder[Coll[Byte]](13)\n val bool31 = box17.tokens(placeholder[Int](14))._1 == coll30\n val bool32 = box17.R6[Int].get == i16\n val bool33 = box12.tokens(placeholder[Int](15))._1 == placeholder[Coll[Byte]](16)\n val bool34 = (box20.tokens(placeholder[Int](17))._1 == coll30) && (box20.R6[Int].get == i14)\n val l35 = SELF.value\n val coll36 = placeholder[Coll[Byte]](18)\n val coll37 = tuple9._1\n if (box1 == SELF) {(\n val box38 = OUTPUTS(placeholder[Int](19))\n val box39 = coll4(placeholder[Int](20))\n val coll40 = box39.tokens\n val l41 = box38.value\n val bi42 = l41.toBigInt - placeholder[Int](21).toBigInt\n val bi43 = box39.R4[Int].get.toBigInt\n val bi44 = box39.value.toBigInt\n val i45 = placeholder[Int](22)\n val tuple46 = box38.R9[(Long, Long)].get\n proveDlog(ge2) && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (box38.propositionBytes == coll3) && (\n (\n coll40(placeholder[Int](23))._2.toBigInt * bi42 * bi43 / bi44 + bi44 * placeholder[Int](24).toBigInt / placeholder[BigInt](\n 25\n ) * i45.toBigInt + bi42 * bi43 > bi24 * l6.toBigInt / i45.toBigInt\n ) && (l41 >= placeholder[Int](26).toLong + placeholder[Long](27))\n )\n ) && (box38.tokens(placeholder[Int](28)) == tuple9)\n ) && (\n (\n (\n (\n (((box38.R4[Coll[Byte]].get == coll25) && (box38.R5[(Int, Int)].get == tuple15)) && (box38.R6[(Long, Long)].get == tuple5)) && (\n box38.R7[Coll[Byte]].get == coll26\n )\n ) && (box38.R8[GroupElement].get == ge2)\n ) && (tuple46._1 == l28)\n ) && (tuple46._2 == l29)\n )\n ) && bool31\n ) && bool32\n ) && bool33\n ) && (coll40(placeholder[Int](29))._1 == coll26)\n ) && bool34\n )\n )} else { if (INPUTS(placeholder[Int](30)) == SELF) {(\n val box38 = OUTPUTS(placeholder[Int](31))\n val coll39 = box38.propositionBytes\n val l40 = box38.value\n val bool41 = l40 >= l35 - placeholder[Long](32)\n val box42 = OUTPUTS(placeholder[Int](33))\n val bool43 = blake2b256(box42.propositionBytes) == placeholder[Coll[Byte]](34)\n val bool44 = box42.value >= placeholder[Int](35).toLong + placeholder[Long](36)\n val coll45 = box42.tokens\n val tuple46 = coll45(placeholder[Int](37))\n val bool47 = tuple46._1 == coll36\n val l48 = tuple46._2\n val tuple49 = coll45(placeholder[Int](38))\n val bool50 = tuple49 == tuple9\n val coll51 = box1.tokens\n val coll52 = box38.tokens\n sigmaProp((((((((((((coll39 == coll25) && bool41) && bool43) && bool44) && (bool47 && (l48.toBigInt > bi24))) && bool50) && bool31) && bool32) && bool33) && bool34) || if (coll51.size >= placeholder[Int](39)) {(\n val bi53 = l35.toBigInt - placeholder[Int](40).toBigInt\n val bi54 = box1.R4[Int].get.toBigInt\n val bi55 = box1.value.toBigInt\n val i56 = placeholder[Int](41)\n val bi57 = coll51(placeholder[Int](42))._2.toBigInt * bi53 * bi54 / bi55 + bi55 * placeholder[Int](43).toBigInt / placeholder[BigInt](44) * i56.toBigInt + bi53 * bi54\n val bi58 = bi57 - bi24\n val bi59 = tuple5._2.toBigInt\n val bi60 = bi58 * i56.toBigInt - bi59 / i56.toBigInt\n ((((((((((((bi57 <= bi24 * l6.toBigInt / i56.toBigInt) && (HEIGHT.toLong >= l29)) || (HEIGHT.toLong > l28)) && bool43) && bool47) && bool44) && if (bi60 < bi7) { l48.toBigInt >= bi57 } else {(\n val box61 = OUTPUTS(placeholder[Int](45))\n val tuple62 = box61.tokens(placeholder[Int](46))\n (((l48.toBigInt >= bi24 + bi58 * bi59 / i56.toBigInt) && (tuple62._2.toBigInt >= bi60)) && (box61.propositionBytes == coll25)) && (tuple62._1 == coll36)\n )}) && bool50) && (coll51(placeholder[Int](47))._1 == coll26)) && bool31) && bool32) && bool33) && bool34\n )} else { placeholder[Boolean](48) }) || if ((coll52.size >= placeholder[Int](49)) && (box1.tokens.size < placeholder[Int](50))) {(\n val tuple53 = box38.R9[(Long, Long)].get\n val l54 = tuple53._2\n val bool55 = coll39 == coll3\n val tuple56 = coll52(placeholder[Int](51))\n val l57 = tuple56._2\n val bi58 = l57.toBigInt\n val bool59 = (((((box38.R4[Coll[Byte]].get == coll25) && (box38.R5[(Int, Int)].get == tuple15)) && (box38.R6[(Long, Long)].get == tuple5)) && (box38.R7[Coll[Byte]].get == coll26)) && (box38.R8[GroupElement].get == ge2)) && (tuple53._1 == l28)\n val box60 = coll4(placeholder[Int](52))\n val coll61 = box60.tokens\n val bi62 = l40.toBigInt - placeholder[Int](53).toBigInt\n val bi63 = box60.R4[Int].get.toBigInt\n val bi64 = box60.value.toBigInt\n val i65 = placeholder[Int](54)\n val bool66 = (coll61(placeholder[Int](55))._2.toBigInt * bi62 * bi63 / bi64 + bi64 * placeholder[Int](56).toBigInt / placeholder[BigInt](57) * i65.toBigInt + bi62 * bi63 >= bi7 + bi58 * bi22 / l23.toBigInt * l6.toBigInt / i65.toBigInt) && (l40 >= placeholder[Int](58).toLong + placeholder[Long](59))\n val bool67 = coll61(placeholder[Int](60))._1 == coll26\n if (l54 == placeholder[Long](61)) { ((((((((((((((bool55 && (l40 >= l35)) && (tuple56._1 == coll37)) && (bi58 >= bi11 - l48.toBigInt * l23.toBigInt / bi22)) && bool59) && (l29 == l54)) && bool43) && bool44) && bool47) && ((tuple49._2 == l10 - l57) && (tuple49._1 == coll37))) && bool31) && bool32) && bool33) && bool34) && bool66) && bool67 } else { (((((((((((!bool66) && bool55) && bool41) && (coll52 == coll8)) && bool59) && ((l54 > HEIGHT.toLong) && (l54 < HEIGHT + placeholder[Int](62).toLong))) && (l29 == placeholder[Long](63))) && bool31) && bool32) && bool33) && bool67) && bool34 }\n )} else { placeholder[Boolean](64) })\n )} else { sigmaProp(placeholder[Boolean](65)) } }\n}",
"address": "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",
"assets": [
{
"tokenId": "1d7857a82d2f3d00d58cbd3b6ad337c98b6aa5e1021a17deb7527e0c3c148be7",
"index": 0,
"amount": 60,
"name": "Borrow Token SigUSD-1e",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "580af601",
"sigmaType": "(SInt, SInt)",
"renderedValue": "[5,123]"
},
"R6": {
"serializedValue": "59c413d804",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1250,300]"
},
"R8": {
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"R8": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R7": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R9": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R4": {
"serializedValue": "11058084af5fd29f9a668c91a16ae088b96c92e6a166",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000,107169769,111420486,113713712,107231625]"
}
}
},
{
"boxId": "3e5341304f204b0c8b226ec08642fa23cb60317df0e39518b320b4a12c7a6d77",
"value": 185860315139058,
"index": 3,
"outputBlockId": "26a4cba848eced46a97722d7fa97bb1f8969fd6b75ddae30383a572807a31ba5",
"outputTransactionId": "eb6cc777994128692e3f207de705cd2430d4e8a7e22e52f68ffc8589a0de2a9f",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "04c60f",
"sigmaType": "SInt",
"renderedValue": "995"
}
}
}
],
"outputs": [
{
"boxId": "59c57ba715a12531ffb6af05d4437dc1e65de07d477140327c861913d906042b",
"transactionId": "1d0611079eaf9edfc66b733a3cd2521dd71e8b5b24332e95e84f264ef5295617",
"blockId": "e5e70e3aaeef26b0a317d915058ab4e7ca8af7597a1b5ee205335f727e7211b5",
"value": 1300000000,
"index": 0,
"globalIndex": 42024404,
"creationHeight": 1325639,
"settlementHeight": 1325641,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: CBigInt(1)\n2: 0\n3: 1\n4: 0\n5: 100000000\n6: 100000000\n7: 2\n8: 1\n9: 0\n10: 100000000\n11: 100000000\n12: 100000000\n13: Coll(53,-42,-8,-125,-68,-101,9,-50,-55,93,-29,-117,-61,-73,-59,-48,29,81,-101,-120,-83,53,18,-69,-90,100,62,-75,-63,9,7,-128)\n14: 0\n15: 0\n16: Coll(-44,91,-64,7,122,-49,102,-74,14,89,-46,77,24,30,41,87,9,85,-56,48,57,-98,-34,36,77,89,-43,-1,114,106,-47,-114)\n17: 0\n18: Coll(3,-6,-14,-53,50,-97,46,-112,-42,-46,59,88,-39,27,-69,108,4,106,-95,67,38,28,-62,31,82,-5,-30,-126,75,-4,-65,4)\n19: 0\n20: 3\n21: 5000000\n22: 1000\n23: 2\n24: 2\n25: CBigInt(100)\n26: 3000000\n27: 1000000\n28: 0\n29: 0\n30: 1\n31: 0\n32: 1000000\n33: 1\n34: Coll(26,-82,111,-75,-122,125,-117,70,-90,-78,-2,-34,-122,-3,79,-75,-116,-100,-74,48,-124,30,35,-37,11,-95,-61,-46,-95,69,-57,88)\n35: 1000000\n36: 1000000\n37: 1\n38: 0\n39: 3\n40: 5000000\n41: 1000\n42: 2\n43: 2\n44: CBigInt(100)\n45: 2\n46: 0\n47: 0\n48: false\n49: 1\n50: 3\n51: 0\n52: 3\n53: 5000000\n54: 1000\n55: 2\n56: 2\n57: CBigInt(100)\n58: 3000000\n59: 1000000\n60: 0\n61: 100000000\n62: 5\n63: 100000000\n64: false\n65: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val ge2 = SELF.R8[GroupElement].get\n val coll3 = SELF.propositionBytes\n val coll4 = CONTEXT.dataInputs\n val tuple5 = SELF.R6[(Long, Long)].get\n val l6 = tuple5._1\n val bi7 = placeholder[BigInt](1)\n val coll8 = SELF.tokens\n val tuple9 = coll8(placeholder[Int](2))\n val l10 = tuple9._2\n val bi11 = l10.toBigInt\n val box12 = coll4(placeholder[Int](3))\n val coll13 = box12.R4[Coll[Long]].get\n val i14 = coll13.size\n val tuple15 = SELF.R5[(Int, Int)].get\n val i16 = tuple15._1\n val box17 = coll4(placeholder[Int](4))\n val coll18 = box17.R4[Coll[Long]].get\n val l19 = coll18.slice(tuple15._2, coll18.size).fold(placeholder[Long](5), {(tuple19: (Long, Long)) => tuple19._1 * tuple19._2 / placeholder[Long](6) })\n val box20 = coll4(placeholder[Int](7))\n val coll21 = box20.R4[Coll[Long]].get\n val bi22 = if (i14 == i16) { l19 } else {(\n val i22 = i16 + placeholder[Int](8)\n val l23 = coll21.slice(placeholder[Int](9), coll21.size).fold(l19, {(tuple23: (Long, Long)) => tuple23._1 * tuple23._2 / placeholder[Long](10) })\n if (i14 == i22) { l23 } else { coll13.slice(i22, i14).fold(l23, {(tuple24: (Long, Long)) => tuple24._1 * tuple24._2 / placeholder[Long](11) }) }\n )}.toBigInt\n val l23 = placeholder[Long](12)\n val bi24 = bi7 + bi11 * bi22 / l23.toBigInt\n val coll25 = SELF.R4[Coll[Byte]].get\n val coll26 = SELF.R7[Coll[Byte]].get\n val tuple27 = SELF.R9[(Long, Long)].get\n val l28 = tuple27._1\n val l29 = tuple27._2\n val coll30 = placeholder[Coll[Byte]](13)\n val bool31 = box17.tokens(placeholder[Int](14))._1 == coll30\n val bool32 = box17.R6[Int].get == i16\n val bool33 = box12.tokens(placeholder[Int](15))._1 == placeholder[Coll[Byte]](16)\n val bool34 = (box20.tokens(placeholder[Int](17))._1 == coll30) && (box20.R6[Int].get == i14)\n val l35 = SELF.value\n val coll36 = placeholder[Coll[Byte]](18)\n val coll37 = tuple9._1\n if (box1 == SELF) {(\n val box38 = OUTPUTS(placeholder[Int](19))\n val box39 = coll4(placeholder[Int](20))\n val coll40 = box39.tokens\n val l41 = box38.value\n val bi42 = l41.toBigInt - placeholder[Int](21).toBigInt\n val bi43 = box39.R4[Int].get.toBigInt\n val bi44 = box39.value.toBigInt\n val i45 = placeholder[Int](22)\n val tuple46 = box38.R9[(Long, Long)].get\n proveDlog(ge2) && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (box38.propositionBytes == coll3) && (\n (\n coll40(placeholder[Int](23))._2.toBigInt * bi42 * bi43 / bi44 + bi44 * placeholder[Int](24).toBigInt / placeholder[BigInt](\n 25\n ) * i45.toBigInt + bi42 * bi43 > bi24 * l6.toBigInt / i45.toBigInt\n ) && (l41 >= placeholder[Int](26).toLong + placeholder[Long](27))\n )\n ) && (box38.tokens(placeholder[Int](28)) == tuple9)\n ) && (\n (\n (\n (\n (((box38.R4[Coll[Byte]].get == coll25) && (box38.R5[(Int, Int)].get == tuple15)) && (box38.R6[(Long, Long)].get == tuple5)) && (\n box38.R7[Coll[Byte]].get == coll26\n )\n ) && (box38.R8[GroupElement].get == ge2)\n ) && (tuple46._1 == l28)\n ) && (tuple46._2 == l29)\n )\n ) && bool31\n ) && bool32\n ) && bool33\n ) && (coll40(placeholder[Int](29))._1 == coll26)\n ) && bool34\n )\n )} else { if (INPUTS(placeholder[Int](30)) == SELF) {(\n val box38 = OUTPUTS(placeholder[Int](31))\n val coll39 = box38.propositionBytes\n val l40 = box38.value\n val bool41 = l40 >= l35 - placeholder[Long](32)\n val box42 = OUTPUTS(placeholder[Int](33))\n val bool43 = blake2b256(box42.propositionBytes) == placeholder[Coll[Byte]](34)\n val bool44 = box42.value >= placeholder[Int](35).toLong + placeholder[Long](36)\n val coll45 = box42.tokens\n val tuple46 = coll45(placeholder[Int](37))\n val bool47 = tuple46._1 == coll36\n val l48 = tuple46._2\n val tuple49 = coll45(placeholder[Int](38))\n val bool50 = tuple49 == tuple9\n val coll51 = box1.tokens\n val coll52 = box38.tokens\n sigmaProp((((((((((((coll39 == coll25) && bool41) && bool43) && bool44) && (bool47 && (l48.toBigInt > bi24))) && bool50) && bool31) && bool32) && bool33) && bool34) || if (coll51.size >= placeholder[Int](39)) {(\n val bi53 = l35.toBigInt - placeholder[Int](40).toBigInt\n val bi54 = box1.R4[Int].get.toBigInt\n val bi55 = box1.value.toBigInt\n val i56 = placeholder[Int](41)\n val bi57 = coll51(placeholder[Int](42))._2.toBigInt * bi53 * bi54 / bi55 + bi55 * placeholder[Int](43).toBigInt / placeholder[BigInt](44) * i56.toBigInt + bi53 * bi54\n val bi58 = bi57 - bi24\n val bi59 = tuple5._2.toBigInt\n val bi60 = bi58 * i56.toBigInt - bi59 / i56.toBigInt\n ((((((((((((bi57 <= bi24 * l6.toBigInt / i56.toBigInt) && (HEIGHT.toLong >= l29)) || (HEIGHT.toLong > l28)) && bool43) && bool47) && bool44) && if (bi60 < bi7) { l48.toBigInt >= bi57 } else {(\n val box61 = OUTPUTS(placeholder[Int](45))\n val tuple62 = box61.tokens(placeholder[Int](46))\n (((l48.toBigInt >= bi24 + bi58 * bi59 / i56.toBigInt) && (tuple62._2.toBigInt >= bi60)) && (box61.propositionBytes == coll25)) && (tuple62._1 == coll36)\n )}) && bool50) && (coll51(placeholder[Int](47))._1 == coll26)) && bool31) && bool32) && bool33) && bool34\n )} else { placeholder[Boolean](48) }) || if ((coll52.size >= placeholder[Int](49)) && (box1.tokens.size < placeholder[Int](50))) {(\n val tuple53 = box38.R9[(Long, Long)].get\n val l54 = tuple53._2\n val bool55 = coll39 == coll3\n val tuple56 = coll52(placeholder[Int](51))\n val l57 = tuple56._2\n val bi58 = l57.toBigInt\n val bool59 = (((((box38.R4[Coll[Byte]].get == coll25) && (box38.R5[(Int, Int)].get == tuple15)) && (box38.R6[(Long, Long)].get == tuple5)) && (box38.R7[Coll[Byte]].get == coll26)) && (box38.R8[GroupElement].get == ge2)) && (tuple53._1 == l28)\n val box60 = coll4(placeholder[Int](52))\n val coll61 = box60.tokens\n val bi62 = l40.toBigInt - placeholder[Int](53).toBigInt\n val bi63 = box60.R4[Int].get.toBigInt\n val bi64 = box60.value.toBigInt\n val i65 = placeholder[Int](54)\n val bool66 = (coll61(placeholder[Int](55))._2.toBigInt * bi62 * bi63 / bi64 + bi64 * placeholder[Int](56).toBigInt / placeholder[BigInt](57) * i65.toBigInt + bi62 * bi63 >= bi7 + bi58 * bi22 / l23.toBigInt * l6.toBigInt / i65.toBigInt) && (l40 >= placeholder[Int](58).toLong + placeholder[Long](59))\n val bool67 = coll61(placeholder[Int](60))._1 == coll26\n if (l54 == placeholder[Long](61)) { ((((((((((((((bool55 && (l40 >= l35)) && (tuple56._1 == coll37)) && (bi58 >= bi11 - l48.toBigInt * l23.toBigInt / bi22)) && bool59) && (l29 == l54)) && bool43) && bool44) && bool47) && ((tuple49._2 == l10 - l57) && (tuple49._1 == coll37))) && bool31) && bool32) && bool33) && bool34) && bool66) && bool67 } else { (((((((((((!bool66) && bool55) && bool41) && (coll52 == coll8)) && bool59) && ((l54 > HEIGHT.toLong) && (l54 < HEIGHT + placeholder[Int](62).toLong))) && (l29 == placeholder[Long](63))) && bool31) && bool32) && bool33) && bool67) && bool34 }\n )} else { placeholder[Boolean](64) })\n )} else { sigmaProp(placeholder[Boolean](65)) } }\n}",
"address": "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",
"assets": [
{
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}
],
"additionalRegisters": {
"R5": {
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"sigmaType": "(SInt, SInt)",
"renderedValue": "[5,123]"
},
"R6": {
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"sigmaType": "(SLong, SLong)",
"renderedValue": "[1250,300]"
},
"R8": {
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"sigmaType": "SGroupElement",
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},
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"sigmaType": "Coll[SByte]",
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},
"R9": {
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"sigmaType": "(SLong, SLong)",
"renderedValue": "[1391134,100000000]"
},
"R4": {
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"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
},
"spentTransactionId": "2c350ac762f6bd94bf1f3037b3433d9ea7548c1862e566be8d5f896372b04f6b",
"mainChain": true
},
{
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"transactionId": "1d0611079eaf9edfc66b733a3cd2521dd71e8b5b24332e95e84f264ef5295617",
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"value": 10079501821015,
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"globalIndex": 42024405,
"creationHeight": 1325639,
"settlementHeight": 1325641,
"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
"assets": [
{
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{
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{
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{
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{
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{
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{
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