Transaction
ID: 43ea5dfb00...bd41
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.69740716 ERG
Tokens:
Loading assets...
Outputs (4)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0016 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0014 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.69630716 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 132,184
Total coins transferred: 0.70040716 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000001005 ERG
Raw Transaction Data
{
"id": "43ea5dfb00431de72b265ee69161d42b67a4ae426d4d5cf0b0562c8a1140bd41",
"blockId": "994dc5a48c0ffffcb206b6e0672814035ec7bea8f9c0495d5ff9d226ae955953",
"inclusionHeight": 1627493,
"timestamp": 1759673617760,
"index": 8,
"globalIndex": 9573178,
"numConfirmations": 132184,
"inputs": [
{
"boxId": "0dc023e378c3681ec847ddac0330e278282b163f76dafacfc08afa7623eb2536",
"value": 1000000,
"index": 0,
"spendingProof": "c749f6ad99596c1752ea914b8471769137be258812cba76aa3e1fdfbcc111feb6652303da57f75e2f7b137acafa392f9ad914cf761208690",
"outputBlockId": "5fad0e0ab67e5eaf0e1e4b5453eea4e3834c16e81ed32c98333c37a5a90210c0",
"outputTransactionId": "888a18adee6e7b8cd1b740c02517286dc02d3b6b4c68ecc2e223cdea0c21de52",
"outputIndex": 0,
"outputGlobalIndex": 50654669,
"outputCreatedAt": 1627435,
"outputSettledAt": 1627437,
"ergoTree": "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",
"ergoTreeConstants": "0: 3\n1: Coll(98,85,-17,66,-84,-62,57,124,-29,-65,8,40,-83,-49,-14,112,-52,37,-32,101,-56,38,33,-77,57,-121,-89,-84,83,-1,41,38)\n2: 0\n3: 0\n4: 1\n5: Coll(0,8,-51)\n6: SigmaProp(ProveDlog(ECPoint(1bf847,c2be87,...)))\n7: 0\n8: 0\n9: false\n10: 1\n11: 1\n12: 1\n13: 1\n14: 0\n15: 0\n16: -1\n17: false\n18: true\n19: -1\n20: 1\n21: 0\n22: true\n23: 1\n24: 0\n25: 0\n26: 1\n27: 2\n28: 2\n29: 3\n30: false\n31: false\n32: false\n33: false\n34: false\n35: 0\n36: Coll(47,118,46,-91,-45,7,77,49,21,-3,101,-98,-18,52,34,54,78,-78,106,-125,110,51,90,-38,-17,-46,-34,56,-2,-124,-102,-75)\n37: 0\n38: 0\n39: 2\n40: 1\n41: false\n42: 0\n43: 1\n44: 0\n45: Coll(-10,-127,-98,11,124,-7,-100,-116,120,114,-74,47,73,-123,-72,-39,0,-58,21,9,37,-48,30,-78,121,120,117,23,-88,72,-74,-40)\n46: 1\n47: 0\n48: 1\n49: 0\n50: 3\n51: 30\n52: -1\n53: -1\n54: false\n55: true\n56: 1\n57: false\n58: false\n59: false\n60: 0\n61: 0\n62: 0\n63: 100\n64: 5\n65: 100\n66: 1000000\n67: 1000000\n68: 0\n69: 0\n70: 0\n71: 1000000\n72: 0\n73: 0\n74: true\n75: 0\n76: true\n77: 0\n78: true\n79: false\n80: 5\n81: 100\n82: 1000000\n83: 0\n84: 0\n85: 1\n86: 0\n87: 0\n88: true\n89: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R7[Coll[Long]].get\n val l4 = coll3(placeholder[Int](0))\n val bool5 = l2 < l4\n val coll6 = placeholder[Coll[Byte]](1)\n val coll7 = SELF.tokens(placeholder[Int](2))._1\n val tuple8 = SELF.R5[(Coll[Byte], Coll[Byte])].get\n val coll9 = tuple8._2\n val l10 = coll3(placeholder[Int](3))\n val coll11 = tuple8._1\n val coll12 = SELF.R6[Coll[Coll[Byte]]].get\n val l13 = coll3(placeholder[Int](4))\n val tuple14 = SELF.R8[(Coll[Byte], Long)].get\n val l15 = tuple14._2\n val coll16 = placeholder[Coll[Byte]](5)\n val coll17 = tuple14._1\n val prop18 = placeholder[SigmaProp](6)\n val bool19 = coll9 != Coll[Byte]()\n val prop20 = if (bool19) {(\n val coll20 = INPUTS.filter({(box20: Box) => (blake2b256(box20.propositionBytes) == coll6) && (box20.R5[Coll[Byte]].get == coll9) })\n if (coll20.size > placeholder[Int](7)) { proveDlog(coll20(placeholder[Int](8)).R4[GroupElement].get) } else { sigmaProp(placeholder[Boolean](9)) }\n )} else { proveDlog(decodePoint(coll17)) }\n sigmaProp(i1 == placeholder[Int](10)) && sigmaProp(if ((bool5 && (INPUTS.size > placeholder[Int](11))) && (OUTPUTS.size > placeholder[Int](12))) {(\n val coll21 = CONTEXT.dataInputs\n val coll22 = coll21.filter({(box22: Box) => ((blake2b256(box22.propositionBytes) == coll6) && (box22.R6[Coll[Byte]].get == coll7)) && (box22.R5[Coll[Byte]].get != coll9) })\n if (coll22.size == placeholder[Int](13)) {(\n val box23 = coll22(placeholder[Int](14))\n val box24 = OUTPUTS(placeholder[Int](15))\n if (((blake2b256(box23.propositionBytes) == coll6) && (box23.R6[Coll[Byte]].get == coll7)) && (box23.creationInfo._1.toLong < l10)) {(\n val tuple25 = (placeholder[Long](16), placeholder[Boolean](17))\n val l26 = box23.R9[Coll[Long]].get.fold(tuple25, {(tuple26: ((Long, Boolean), Long)) =>\n val tuple28 = tuple26._1\n val l29 = tuple26._2\n if (tuple28._2) { tuple28 } else { if (blake2b256(box23.R7[Coll[Byte]].get.append(longToByteArray(l29)).append(box23.R8[Coll[Byte]].get).append(coll11)) == box23.R5[Coll[Byte]].get) { (l29, placeholder[Boolean](18)) } else { tuple28 } }\n })._1\n val bool27 = l26 != placeholder[Long](19)\n if (bool27) {(\n val coll28 = Coll[Byte]()\n val coll29 = if (coll9 == coll28) { box23.R5[Coll[Byte]].get } else {(\n val coll29 = coll21.filter({(box29: Box) => ((blake2b256(box29.propositionBytes) == coll6) && (box29.R5[Coll[Byte]].get == coll9)) && (box29.R6[Coll[Byte]].get == coll7) })\n if (coll29.size == placeholder[Int](20)) {(\n val box30 = coll29(placeholder[Int](21))\n val l31 = box30.R9[Coll[Long]].get.fold(tuple25, {(tuple31: ((Long, Boolean), Long)) =>\n val tuple33 = tuple31._1\n val l34 = tuple31._2\n if (tuple33._2) { tuple33 } else { if (blake2b256(box30.R7[Coll[Byte]].get.append(longToByteArray(l34)).append(box30.R8[Coll[Byte]].get).append(coll11)) == box30.R5[Coll[Byte]].get) { (l34, placeholder[Boolean](22)) } else { tuple33 } }\n })._1\n if ((l26 > l31) || ((l26 == l31) && (box23.creationInfo._1 < box30.creationInfo._1))) { box23.R5[Coll[Byte]].get } else { coll28 }\n )} else { coll28 }\n )}\n if ((coll29 != coll28) && (coll29 != coll9)) { ((((((((((((box24.propositionBytes == SELF.propositionBytes) && (box24.R4[Int].get == i1)) && (box24.tokens.size == placeholder[Int](23))) && (box24.tokens(placeholder[Int](24))._1 == coll7)) && (box24.R5[(Coll[Byte], Coll[Byte])].get == (coll11, coll29))) && (box24.R6[Coll[Coll[Byte]]].get == coll12)) && (box24.R7[Coll[Long]].get(placeholder[Int](25)) == l10)) && (box24.R7[Coll[Long]].get(placeholder[Int](26)) == l13)) && (box24.R7[Coll[Long]].get(placeholder[Int](27)) == coll3(placeholder[Int](28)))) && (box24.R7[Coll[Long]].get(placeholder[Int](29)) == l4)) && (box24.R8[(Coll[Byte], Long)].get._2 == l15)) && (box24.R9[(Coll[Byte], Coll[Byte])].get == SELF.R9[(Coll[Byte], Coll[Byte])].get)) && bool27 } else { placeholder[Boolean](30) }\n )} else { placeholder[Boolean](31) }\n )} else { placeholder[Boolean](32) }\n )} else { placeholder[Boolean](33) }\n )} else { placeholder[Boolean](34) }) || sigmaProp(if (bool5 && (CONTEXT.dataInputs.size > placeholder[Int](35))) {(\n val coll21 = CONTEXT.dataInputs\n val coll22 = coll21.filter({(box22: Box) => blake2b256(box22.propositionBytes) == placeholder[Coll[Byte]](36) })\n val i23 = coll22.size\n val i24 = coll12.size\n val coll25 = OUTPUTS.filter({(box25: Box) => box25.propositionBytes == SELF.propositionBytes })\n if (if (i23 < if (i24 == placeholder[Int](37)) { placeholder[Int](38) } else { i24 / placeholder[Int](39) + placeholder[Int](40) }) { placeholder[Boolean](41) } else {(\n val coll26 = coll22.map({(box26: Box) => box26.tokens(placeholder[Int](42))._1 })\n coll26.indices.forall({(i27: Int) => !coll26.slice(i27 + placeholder[Int](43), i23).exists({(coll29: Coll[Byte]) => coll29 == coll26(i27) }) }) && coll22.forall({(box27: Box) => (coll12.exists({(coll29: Coll[Byte]) => coll29 == box27.tokens(placeholder[Int](44))._1 }) && (box27.R4[Coll[Byte]].get == placeholder[Coll[Byte]](45))) && (box27.R5[Coll[Byte]].get == coll9) })\n )} && (coll25.size == placeholder[Int](46))) {(\n val coll26 = INPUTS.filter({(box26: Box) => (blake2b256(box26.propositionBytes) == coll6) && (box26.R5[Coll[Byte]].get == coll9) })\n val box27 = coll25(placeholder[Int](47))\n if (coll26.size == placeholder[Int](48)) { (((box27.value >= SELF.value + coll26(placeholder[Int](49)).value) && (box27.R7[Coll[Long]].get(placeholder[Int](50)) >= l4 + placeholder[Long](51))) && (box27.R5[(Coll[Byte], Coll[Byte])].get._2 == coll21.filter({(box28: Box) => blake2b256(box28.propositionBytes) == coll6 }).fold((placeholder[Long](52), Coll[Byte]()), {(tuple28: ((Long, Coll[Byte]), Box)) =>\n val box30 = tuple28._2\n val coll31 = box30.R5[Coll[Byte]].get\n val tuple32 = tuple28._1\n if (coll31 != coll9) {(\n val l33 = box30.R9[Coll[Long]].get.fold((placeholder[Long](53), placeholder[Boolean](54)), {(tuple33: ((Long, Boolean), Long)) =>\n val tuple35 = tuple33._1\n val l36 = tuple33._2\n if (tuple35._2) { tuple35 } else { if (blake2b256(box30.R7[Coll[Byte]].get.append(longToByteArray(l36)).append(box30.R8[Coll[Byte]].get).append(coll11)) == coll31) { (l36, placeholder[Boolean](55)) } else { tuple35 } }\n })._1\n if (l33 > tuple32._1) { (l33, coll31) } else { tuple32 }\n )} else { tuple32 }\n })._2)) && ((box27.R4[Int].get == i1) && (i1 == placeholder[Int](56))) } else { placeholder[Boolean](57) }\n )} else { placeholder[Boolean](58) }\n )} else { placeholder[Boolean](59) }) || if ((l2 >= l4) && (OUTPUTS.size > placeholder[Int](60))) {(\n val coll21 = INPUTS.filter({(box21: Box) => blake2b256(box21.propositionBytes) == coll6 })\n val l22 = coll21.fold(placeholder[Long](61), {(tuple22: (Long, Box)) => tuple22._1 + tuple22._2.value })\n if (bool19) { if (coll21.filter({(box23: Box) => box23.R5[Coll[Byte]].get == coll9 }).size > placeholder[Int](62)) {(\n val l23 = l22 * l15 / placeholder[Long](63)\n val l24 = l22 * placeholder[Long](64) / placeholder[Long](65)\n val bool25 = l22 - l23 - l24 >= placeholder[Long](66)\n val l26 = if (bool25) { l13 + l23 } else { l13 }\n val l27 = l26 - if ((l26 < placeholder[Long](67)) && (l26 > placeholder[Long](68))) { l26 } else { placeholder[Long](69) }\n val l28 = if (bool25) { l24 } else { placeholder[Long](70) }\n val l29 = l28 - if ((l28 < placeholder[Long](71)) && (l28 > placeholder[Long](72))) { l28 } else { placeholder[Long](73) }\n prop20 && sigmaProp((placeholder[Boolean](74) && if (l27 > placeholder[Long](75)) { OUTPUTS.exists({(box30: Box) => (box30.value >= l27) && (box30.propositionBytes == coll16.append(coll17)) }) } else { placeholder[Boolean](76) }) && if (l29 > placeholder[Long](77)) { OUTPUTS.exists({(box30: Box) => (box30.value >= l29) && (box30.propositionBytes == prop18.propBytes) }) } else { placeholder[Boolean](78) })\n )} else { sigmaProp(placeholder[Boolean](79)) } } else {(\n val l23 = l22 * placeholder[Long](80) / placeholder[Long](81)\n val l24 = l23 - if ((l23 < placeholder[Long](82)) && (l23 > placeholder[Long](83))) { l23 } else { placeholder[Long](84) }\n prop20 && sigmaProp(\n OUTPUTS.exists(\n {(box25: Box) =>\n (((box25.value >= l22 + l13 - l24) && (box25.propositionBytes == coll16.append(coll17))) && (box25.tokens.size == placeholder[Int](85))) && (\n box25.tokens(placeholder[Int](86))._1 == coll7\n )\n }\n ) && if (l24 > placeholder[Long](87)) { OUTPUTS.exists({(box25: Box) => (box25.value >= l24) && (box25.propositionBytes == prop18.propBytes) }) } else {\n placeholder[Boolean](88)\n }\n )\n )}\n )} else { sigmaProp(placeholder[Boolean](89)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "cdca7d850f29ccf7bc66409ce9139229a29f8d2cdd8374263fa57dff97502216",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "3c0e0e2035aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21204f398857859df5d15a1785415394db3c6dad602b46dc9b133206865bed2424a5",
"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[35aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21,4f398857859df5d15a1785415394db3c6dad602b46dc9b133206865bed2424a5]"
},
"R6": {
"serializedValue": "1a0120064a0006b870674e3ad37f3a55692d4eaaa501b96065dc43f12bd29ca9ca53aa",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[064a0006b870674e3ad37f3a55692d4eaaa501b96065dc43f12bd29ca9ca53aa]"
},
"R8": {
"serializedValue": "4d0e2102910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b728",
"sigmaType": "(Coll[SByte], SLong)",
"renderedValue": "[02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7,20]"
},
"R7": {
"serializedValue": "1105d2d4c60180897a80897aa6d5c60104",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1627433,1000000,1000000,1627475,2]"
},
"R9": {
"serializedValue": "3c0e0e2102910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b79e017b227469746c65223a2254657374205634222c226465736372697074696f6e223a22222c22696d61676555524c223a22222c227765624c696e6b223a22222c22736572766963654964223a2264313961336461376435613230326631316133306463353537633237636130666161313735656435396565356661636564373265366362323638353862373264222c226d6972726f7255726c73223a5b5d7d",
"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7,7b227469746c65223a2254657374205634222c226465736372697074696f6e223a22222c22696d61676555524c223a22222c227765624c696e6b223a22222c22736572766963654964223a2264313961336461376435613230326631316133306463353537633237636130666161313735656435396565356661636564373265366362323638353862373264222c226d6972726f7255726c73223a5b5d7d]"
},
"R4": {
"serializedValue": "0402",
"sigmaType": "SInt",
"renderedValue": "1"
}
}
},
{
"boxId": "88d556946ee9f56bbc0b68ecac4649263a8b9b171503e480bbb7dcf8f9e8ed9b",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "ba965975c4d641b1962f59991db6c314bf1dde29e7fc56062951a87a7b274e87",
"outputTransactionId": "e0b587bb45c9eacefd2c62de7b42cf580b8b079bfd95ed01cfdb243ceab8f88e",
"outputIndex": 0,
"outputGlobalIndex": 50654480,
"outputCreatedAt": 1627429,
"outputSettledAt": 1627430,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 1\n4: 1\n5: 0\n6: 1\n7: 1\n8: 0\n9: 1\n10: 1\n11: 0\n12: 2\n13: 1\n14: false\n15: 0\n16: 0\n17: 0\n18: 2\n19: false\n20: 1\n21: 0\n22: 0\n23: 1\n24: 0\n25: 0\n26: 720\n27: false\n28: false\n29: 1\n30: 0\n31: 0\n32: 1\n33: 3\n34: false\n35: 1\n36: 0\n37: 3\n38: 1\n39: 0\n40: 4\n41: 4\n42: 1\n43: false\n44: false\n45: 1\n46: 0\n47: 3\n48: 64800\n49: Coll(0,8,-51)\n50: false\n51: false",
"ergoTreeScript": "{\n val coll1 = CONTEXT.dataInputs\n val bool2 = coll1.size > placeholder[Int](0)\n val coll3 = SELF.R6[Coll[Byte]].get\n val ge4 = SELF.R4[GroupElement].get\n val coll5 = INPUTS.filter({(box5: Box) =>\n val coll7 = box5.tokens\n ((coll7.size == placeholder[Int](1)) && (coll7(placeholder[Int](2))._1 == coll3)) && (box5.R4[Int].get == placeholder[Int](3))\n })\n val coll6 = INPUTS.filter({(box6: Box) =>\n val coll8 = box6.tokens\n ((coll8.size == placeholder[Int](4)) && (coll8(placeholder[Int](5))._1 == coll3)) && (box6.R4[Int].get == placeholder[Int](6))\n })\n val coll7 = coll1.filter({(box7: Box) =>\n val coll9 = box7.tokens\n ((coll9.size == placeholder[Int](7)) && (coll9(placeholder[Int](8))._1 == coll3)) && (box7.R4[Int].get == placeholder[Int](9))\n })\n if (bool2) {(\n val coll8 = coll1.filter({(box8: Box) =>\n val coll10 = box8.tokens\n ((coll10.size == placeholder[Int](10)) && (coll10(placeholder[Int](11))._1 == coll3)) && (box8.R4[Int].get == placeholder[Int](12))\n })\n if (coll8.size != placeholder[Int](13)) { sigmaProp(placeholder[Boolean](14)) } else {(\n val box9 = coll8(placeholder[Int](15))\n val coll10 = box9.tokens\n sigmaProp(\n (((coll10.size > placeholder[Int](16)) && (coll10(placeholder[Int](17))._1 == coll3)) && box9.R6[Coll[Byte]].isDefined) && (\n box9.R4[Int].get == placeholder[Int](18)\n )\n ) && proveDlog(ge4)\n )}\n )} else { sigmaProp(placeholder[Boolean](19)) } || if (bool2) {(\n val coll8 = coll1.filter({(box8: Box) =>\n val coll10 = box8.tokens\n ((coll10.size == placeholder[Int](20)) && (coll10(placeholder[Int](21))._1 == coll3)) && (box8.R4[Int].get == placeholder[Int](22))\n })\n if (coll8.size == placeholder[Int](23)) {\n sigmaProp(HEIGHT.toLong >= coll8(placeholder[Int](24)).R8[Coll[Long]].get(placeholder[Int](25)) + placeholder[Long](26)) && proveDlog(ge4)\n } else { sigmaProp(placeholder[Boolean](27)) }\n )} else { sigmaProp(placeholder[Boolean](28)) } || sigmaProp(if (coll5.size == placeholder[Int](29)) {(\n val box8 = coll5(placeholder[Int](30))\n ((box8.tokens(placeholder[Int](31))._1 == coll3) && (box8.R4[Int].get == placeholder[Int](32))) && (HEIGHT.toLong >= box8.R7[Coll[Long]].get(placeholder[Int](33)))\n )} else { placeholder[Boolean](34) }) || sigmaProp(if (coll6.size == placeholder[Int](35)) {(\n val box8 = coll6(placeholder[Int](36))\n val coll9 = box8.R7[Coll[Long]].get\n val coll10 = box8.R5[(Coll[Byte], Coll[Byte])].get._2\n val coll11 = OUTPUTS.filter({(box11: Box) => box11.propositionBytes == box8.propositionBytes })\n if (((HEIGHT.toLong < coll9(placeholder[Int](37))) && (SELF.R5[Coll[Byte]].get == coll10)) && (coll11.size == placeholder[Int](38))) {(\n val box12 = coll11(placeholder[Int](39))\n ((box12.R7[Coll[Long]].get(placeholder[Int](40)) == coll9(placeholder[Int](41)) - placeholder[Long](42)) && (box12.value >= box8.value + SELF.value)) && (box12.R5[(Coll[Byte], Coll[Byte])].get._2 != coll10)\n )} else { placeholder[Boolean](43) }\n )} else { placeholder[Boolean](44) }) || if (coll7.size == placeholder[Int](45)) {(\n val box8 = coll7(placeholder[Int](46))\n if (HEIGHT.toLong >= box8.R7[Coll[Long]].get(placeholder[Int](47)) + placeholder[Long](48)) {(\n val coll9 = box8.R8[(Coll[Byte], Long)].get._1\n proveDlog(decodePoint(coll9)) && sigmaProp(\n OUTPUTS.exists({(box10: Box) => (box10.propositionBytes == placeholder[Coll[Byte]](49).append(coll9)) && (box10.value >= SELF.value) })\n )\n )} else { sigmaProp(placeholder[Boolean](50)) }\n )} else { sigmaProp(placeholder[Boolean](51)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "0e204f398857859df5d15a1785415394db3c6dad602b46dc9b133206865bed2424a5",
"sigmaType": "Coll[SByte]",
"renderedValue": "4f398857859df5d15a1785415394db3c6dad602b46dc9b133206865bed2424a5"
},
"R6": {
"serializedValue": "0e20cdca7d850f29ccf7bc66409ce9139229a29f8d2cdd8374263fa57dff97502216",
"sigmaType": "Coll[SByte]",
"renderedValue": "cdca7d850f29ccf7bc66409ce9139229a29f8d2cdd8374263fa57dff97502216"
},
"R8": {
"serializedValue": "0e2004af1393b0fd55e2ec88354b9bac87400161207dda7e20d00c82ab083cd3acf9",
"sigmaType": "Coll[SByte]",
"renderedValue": "04af1393b0fd55e2ec88354b9bac87400161207dda7e20d00c82ab083cd3acf9"
},
"R7": {
"serializedValue": "0e20f570c45bcc26cdeaf9658212eadd6a82659944c407a19953104c0d59d4d50734",
"sigmaType": "Coll[SByte]",
"renderedValue": "f570c45bcc26cdeaf9658212eadd6a82659944c407a19953104c0d59d4d50734"
},
"R9": {
"serializedValue": "11069003c80104d804f601b401",
"sigmaType": "Coll[SLong]",
"renderedValue": "[200,100,2,300,123,90]"
},
"R4": {
"serializedValue": "0702910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"sigmaType": "SGroupElement",
"renderedValue": "02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7"
}
}
},
{
"boxId": "a057bb1eda44ce87d1e5aee419c8ed4a035542a90c35cfd4002d90b84874ba4c",
"value": 1000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "ba965975c4d641b1962f59991db6c314bf1dde29e7fc56062951a87a7b274e87",
"outputTransactionId": "7d6003146c855018129aec31d48cbfa47c910b27db52c6dcbfc94b5ddf1384a8",
"outputIndex": 0,
"outputGlobalIndex": 50654487,
"outputCreatedAt": 1627429,
"outputSettledAt": 1627430,
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"assets": [],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "773511d4ff3d40d887cb7f693376f84bc8ad92812ac5dc499333b9c2f7f926e8"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "cdca7d850f29ccf7bc66409ce9139229a29f8d2cdd8374263fa57dff97502216"
},
"R8": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b111e17c09aa19c1e21738c3ff24ff81bec223d093b1faf52271cc93d932bd79"
},
"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "c5f7eaa580cbbcd782a02e1593c0f1972d02d5583f9fb60b9c7f5e2db0d2c41f"
},
"R9": {
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"sigmaType": "Coll[SLong]",
"renderedValue": "[50,600,120,30,50,60]"
},
"R4": {
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"sigmaType": "SGroupElement",
"renderedValue": "02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7"
}
}
},
{
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"outputIndex": 3,
"outputGlobalIndex": 50654868,
"outputCreatedAt": 1627440,
"outputSettledAt": 1627441,
"ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
"address": "9fcwctfPQPkDfHgxBns5Uu3dwWpaoywhkpLEobLuztfQuV5mt3T",
"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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{
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{
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{
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{
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],
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}
],
"dataInputs": [],
"outputs": [
{
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