Transaction
ID: 51fc2e8a7f...43ff
Inputs (6)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.1032 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
0
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
0
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0042 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
2.1 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.061 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.04 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
1
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0022 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.11 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 22,241
Total coins transferred: 2.21 ERG
Fees: 0.0022 ERG
Fees per byte: 0.000000562 ERG
Raw Transaction Data
{
"id": "51fc2e8a7f769cba634c43a73924683aae8d8f3489133bff70917b262d7043ff",
"blockId": "af6da11c730fddb471341cfa4786567ff58344ffb5ccf342c2465b4d3436a00e",
"inclusionHeight": 1746847,
"timestamp": 1774110497579,
"index": 11,
"globalIndex": 10479341,
"numConfirmations": 22241,
"inputs": [
{
"boxId": "b4e8d6a9a15e492e0ef0388d0ca9900ae907e33abf6de7e18c424923a4a090dd",
"value": 103200000,
"index": 0,
"spendingProof": null,
"outputBlockId": "9dac7ee6c37c53a48fa22dea18806a58c73de294f713f63908e887501a8fa799",
"outputTransactionId": "bf11c4ddd71da7528cf837c1b862528af0f5b8fa85801a588449f247a7e88ee2",
"outputIndex": 0,
"outputGlobalIndex": 54264306,
"outputCreatedAt": 1746842,
"outputSettledAt": 1746844,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 8\n5: 7\n6: Coll(-22,123,54,-30,-108,-79,-87,84,-88,7,82,-22,-62,-120,113,23,40,-27,-71,27,11,60,5,-106,84,-116,117,86,101,5,11,-120)\n7: 0\n8: Coll(-91,91,-121,53,-19,26,-103,-28,108,44,-119,-8,-103,74,-84,-33,75,17,9,-67,-49,104,47,30,91,52,71,-100,110,57,38,105)\n9: 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)\n10: 10\n11: 4\n12: 6\n13: 1000000\n14: false\n15: 5\n16: 0\n17: 1\n18: 2\n19: 9\n20: 1\n21: 1\n22: 1\n23: 0\n24: 3\n25: 5\n26: 1\n27: 0\n28: 0\n29: 1\n30: 2\n31: 1\n32: 3\n33: 0\n34: 1000000\n35: 0\n36: 0\n37: 0\n38: 17\n39: 0\n40: 0\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 0\n47: 1000\n48: 100\n49: 1000\n50: 0\n51: 100\n52: 0\n53: 2\n54: 0\n55: 17\n56: 1\n57: 2\n58: 17\n59: 0\n60: 17\n61: 1000000\n62: 0\n63: 3\n64: 2000000\n65: 1\n66: 1\n67: 1\n68: 1\n69: 2\n70: 1\n71: 1000000\n72: 0\n73: 1\n74: 2\n75: 1\n76: 0\n77: false\n78: 1\n79: 3\n80: 1000000\n81: 1\n82: 1000000\n83: 1\n84: 1\n85: false\n86: 0\n87: 0\n88: 0\n89: 0\n90: 0\n91: 1000000\n92: 1000000\n93: 0\n94: 0\n95: 1000\n96: 0\n97: 17\n98: 0\n99: 17\n100: 2\n101: 1\n102: 2\n103: 0\n104: true\n105: 1\n106: 2\n107: 0\n108: true\n109: false\n110: 1\n111: 0\n112: 1\n113: 0\n114: 0\n115: 0\n116: 0\n117: 1000000\n118: 0\n119: Coll(49,-126,103,79,7,-37,-71,-115,105,109,56,-19,-91,62,99,-21,59,-11,-2,87,15,113,-34,-24,94,-71,84,-42,-49,-112,59,-70)\n120: 0\n121: 0\n122: 0\n123: true\n124: false\n125: 2\n126: false",
"ergoTreeScript": "{\n val coll1 = SELF.R9[Coll[Coll[Byte]]].get\n val prop2 = proveDlog(decodePoint(coll1(placeholder[Int](0))))\n val coll3 = SELF.tokens\n val tuple4 = (Coll[Byte](), placeholder[Long](1))\n val tuple5 = coll3.getOrElse(placeholder[Int](2), tuple4)\n val coll6 = tuple5._1\n val coll7 = SELF.R7[Coll[Byte]].get\n val bool8 = coll6 == coll7\n val bool9 = !bool8\n val box10 = OUTPUTS(placeholder[Int](3))\n val coll11 = box10.propositionBytes\n val coll12 = prop2.propBytes\n val coll13 = SELF.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](4))\n val l15 = coll13(placeholder[Int](5))\n val coll16 = placeholder[Coll[Byte]](6)\n val l17 = coll13(placeholder[Int](7))\n val coll18 = placeholder[Coll[Byte]](8)\n val coll19 = placeholder[Coll[Byte]](9)\n val l20 = coll13(placeholder[Int](10))\n val l21 = coll13(placeholder[Int](11))\n val l22 = coll13(placeholder[Int](12))\n val l23 = l22 + placeholder[Long](13)\n val coll24 = SELF.R5[Coll[Byte]].get\n val bool25 = if (coll11 == SELF.propositionBytes) {\n (\n (\n (((box10.value >= l23) && (box10.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box10.R5[Coll[Byte]].get == coll24)) && (\n box10.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get\n )\n ) && (box10.R8[Coll[Long]].get == coll13)\n ) && (box10.R9[Coll[Coll[Byte]]].get == coll1)\n } else { placeholder[Boolean](14) }\n val coll26 = SELF.id\n val l27 = coll13(placeholder[Int](15))\n val coll28 = box10.tokens\n val tuple29 = coll28.getOrElse(placeholder[Int](16), tuple4)\n val coll30 = tuple29._1\n val tuple31 = coll28.getOrElse(placeholder[Int](17), tuple4)\n val l32 = tuple5._2\n val l33 = coll13(placeholder[Int](18))\n val l34 = tuple29._2\n val coll35 = tuple31._1\n val l36 = coll13(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool8 && (l32 == placeholder[Long](21))\n val tuple40 = coll3.getOrElse(placeholder[Int](22), tuple4)\n val tuple41 = coll38.getOrElse(placeholder[Int](23), tuple4)\n val l42 = HEIGHT.toLong\n val l43 = coll13(placeholder[Int](24))\n val l44 = l43 + placeholder[Long](25)\n val bool45 = if (coll13(placeholder[Int](26)) == placeholder[Long](27)) { (bool39 && (l42 >= l43)) && (l42 <= l44) } else { bool39 && (l42 <= l44) }\n val l46 = INPUTS.fold(placeholder[Long](28), {(tuple46: (Long, Box)) =>\n val box48 = tuple46._2\n val l49 = tuple46._1\n if (box48.id != coll26) { box48.tokens.fold(l49, {(tuple50: (Long, (Coll[Byte], Long))) =>\n val tuple52 = tuple50._2\n val l53 = tuple50._1\n if (tuple52._1 == coll7) { l53 + tuple52._2 } else { l53 }\n }) } else { l49 }\n })\n val bool47 = ((bool25 && (box10.R7[Coll[Byte]].get == coll7)) && \n val coll47 = coll30\n coll47 == coll6\n ) && (l34 == placeholder[Long](29))\n val l48 = tuple31._2\n prop2 && sigmaProp((bool9 && (OUTPUTS.size == placeholder[Int](30))) && (coll11 == coll12)) || sigmaProp(\n (((if ((bool9 && (INPUTS.size == placeholder[Int](31))) && (OUTPUTS.size == placeholder[Int](32))) {(\n val bool49 = l14 == placeholder[Long](33)\n val l50 = l21 * l20 / placeholder[Long](34)\n val bool51 = l50 > placeholder[Long](35)\n ((((((((((if (bool49) {(\n val box52 = CONTEXT.dataInputs(placeholder[Int](36))\n val i53 = l15.toInt\n val l54 = box52.R5[Coll[Long]].get(i53)\n val bool55 = box52.tokens(placeholder[Int](37))._1 == coll16\n val coll56 = box52.R4[Coll[Coll[Byte]]].get(i53)\n if (l15 == placeholder[Long](38)) { bool55 && (l54 > placeholder[Long](39)) } else { if (l17 == placeholder[Long](40)) { ((bool55 && (coll56.size > placeholder[Int](41))) && (l54 > placeholder[Long](42))) && (coll3(placeholder[Int](43))._1 == coll56) } else { (bool55 && (coll56.size > placeholder[Int](44))) && (l54 > placeholder[Long](45)) } }\n )} else {(\n val coll52 = coll3(placeholder[Int](46))._1\n (coll52 == coll18) || (coll52 == coll19)\n )} && if (bool49) { (l20 == placeholder[Long](47)) || (l20 == placeholder[Long](48)) } else { ((l20 == placeholder[Long](49)) && (coll3(placeholder[Int](50))._1 == coll18)) || ((l20 == placeholder[Long](51)) && (coll3(placeholder[Int](52))._1 == coll19)) }) && bool51) && bool25) && (box10.R7[Coll[Byte]].get == coll26)) && (box10.value == SELF.value - l22 - l27)) && (box10.value >= placeholder[Long](53) * l23)) && (coll30 == coll26)) && \n val bool52 = l17 == placeholder[Long](54)\n ((((((((bool52 && bool49) && (l15 != placeholder[Long](55))) && \n val coll53 = coll35\n coll53 == coll24\n ) && (tuple31 == tuple5)) && (l34 == l32 / l33 + placeholder[Long](56))) && (coll28.size == placeholder[Int](57))) || (((bool52 && bool49) && (l15 == placeholder[Long](58))) && \n val l53 = l33 * CONTEXT.dataInputs(placeholder[Int](59)).R5[Coll[Long]].get(placeholder[Int](60)) / placeholder[Long](61)\n val l54 = SELF.value\n (((l53 > placeholder[Long](62)) && (l34 == l54 - placeholder[Long](63) * l22 - l27 - placeholder[Long](64) / l53 + placeholder[Long](65))) && (coll28.size == placeholder[Int](66))) && (box10.value >= l54 - l22 - l27)\n )) || (((((((l17 == placeholder[Long](67)) && bool49) && (coll35 == coll24)) && (tuple31 == tuple5)) && bool51) && (l34 == l32 / l50 + placeholder[Long](68))) && (coll28.size == placeholder[Int](69)))) || ((l14 == placeholder[Long](70)) && \n val l53 = l36 * l20 / placeholder[Long](71)\n ((((l53 > placeholder[Long](72)) && (coll35 == coll24)) && (tuple31 == tuple5)) && (l34 == l32 / l53 + placeholder[Long](73))) && (coll28.size == placeholder[Int](74))\n )\n ) && (box37.propositionBytes == coll1(placeholder[Int](75)))) && (coll38.size == placeholder[Int](76))) && (box37.value >= l27)\n )} else { placeholder[Boolean](77) } || if (((bool8 && (!bool39)) && (INPUTS.size == placeholder[Int](78))) && (OUTPUTS.size == placeholder[Int](79))) { ((((((((((box10.value == SELF.value - l22 - placeholder[Long](80)) && bool25) && (box10.R7[Coll[Byte]].get == coll7)) && (coll30 == coll6)) && (l34 == placeholder[Long](81))) && (tuple31 == tuple40)) && (box37.propositionBytes == coll12)) && (box37.value == placeholder[Long](82))) && (coll38.size == placeholder[Int](83))) && (tuple41._1 == coll6)) && (tuple41._2 == l32 - placeholder[Long](84)) } else { placeholder[Boolean](85) }) || if ((bool45 && (l14 == placeholder[Long](86))) && (l46 > placeholder[Long](87))) {(\n val box49 = CONTEXT.dataInputs(placeholder[Int](88))\n val i50 = l15.toInt\n val l51 = box49.R5[Coll[Long]].get(i50)\n val bool52 = l51 > placeholder[Long](89)\n val bool53 = box49.tokens(placeholder[Int](90))._1 == coll16\n val l54 = l33 * l51 / placeholder[Long](91)\n val l55 = l21 * l20 / placeholder[Long](92)\n val bool56 = (l54 > placeholder[Long](93)) && (l55 > placeholder[Long](94))\n val l57 = l54 * l46\n val coll58 = if (l20 == placeholder[Long](95)) { coll18 } else { coll19 }\n val l59 = l55 * l46\n val coll60 = box49.R4[Coll[Coll[Byte]]].get(i50)\n val bool61 = (coll60.size > placeholder[Int](96)) || (l15 == placeholder[Long](97))\n if (l17 == placeholder[Long](98)) { if (l15 == placeholder[Long](99)) {(\n val box62 = OUTPUTS(placeholder[Int](100))\n (((((bool53 && bool52) && bool56) && (box37.value >= l57)) && ((box62.propositionBytes == coll12) && box62.tokens.exists({(tuple63: (Coll[Byte], Long)) => (tuple63._1 == coll58) && (tuple63._2 >= l59) }))) && bool47) && (box10.value >= SELF.value - l57 - l22)\n )} else {(\n val tuple62 = coll3(placeholder[Int](101))\n val box63 = OUTPUTS(placeholder[Int](102))\n (((((((((bool53 && bool61) && bool52) && bool56) && (tuple62._1 == coll60)) && coll38.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll60) && (tuple64._2 >= l57) })) && ((box63.propositionBytes == coll12) && box63.tokens.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll58) && (tuple64._2 >= l59) }))) && if (l48 > placeholder[Long](103)) { coll35 == coll60 } else { placeholder[Boolean](104) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple62._2 - l57)\n )} } else {(\n val tuple62 = coll3(placeholder[Int](105))\n val coll63 = tuple62._1\n val box64 = OUTPUTS(placeholder[Int](106))\n (((((((((bool53 && bool61) && bool52) && bool56) && ((coll63 == coll18) || (coll63 == coll19))) && coll38.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll63) && (tuple65._2 >= l59) })) && ((box64.propositionBytes == coll12) && box64.tokens.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll60) && (tuple65._2 >= l57) }))) && if (l48 > placeholder[Long](107)) { coll35 == coll63 } else { placeholder[Boolean](108) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple62._2 - l59)\n )}\n )} else { placeholder[Boolean](109) }) || if ((bool45 && (l14 == placeholder[Long](110))) && (l46 > placeholder[Long](111))) {(\n val tuple49 = coll3(placeholder[Int](112))\n val coll50 = tuple49._1\n val box51 = CONTEXT.dataInputs(placeholder[Int](113))\n val l52 = box51.R8[Coll[Long]].get(l15.toInt)\n val l53 = if (l17 == placeholder[Long](114)) { if (l52 > l21) {(\n val l53 = l52 - l21\n if (l53 > l36) { l36 } else { l53 }\n )} else { placeholder[Long](115) } } else { if (l52 < l21) {(\n val l53 = l21 - l52\n if (l53 > l36) { l36 } else { l53 }\n )} else { placeholder[Long](116) } }\n val l54 = l53 * l20 / placeholder[Long](117)\n val l55 = l54 * l46\n (((((((((coll50 == coll18) || (coll50 == coll19)) && (box51.tokens(placeholder[Int](118))._1 == placeholder[Coll[Byte]](119))) && (l53 > placeholder[Long](120))) && (l54 > placeholder[Long](121))) && coll38.exists({(tuple56: (Coll[Byte], Long)) => (tuple56._1 == coll50) && (tuple56._2 >= l55) })) && if (l48 > placeholder[Long](122)) { coll35 == coll50 } else { placeholder[Boolean](123) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple49._2 - l55)\n )} else { placeholder[Boolean](124) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](125)) && (coll11 == coll12)) && (box10.value >= SELF.value - l22)) && (coll30 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](126) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "fbea840eca013808d33ce5ad38ad7ee00e3f4e34f3833c35b6326237e51f377b",
"index": 0,
"amount": 1,
"name": "TEST Multi-Buyer",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0e0139",
"sigmaType": "Coll[SByte]",
"renderedValue": "39"
},
"R8": {
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"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,10000,1746892,200000,1000000,2200000,17,0,0,1000]"
},
"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "fbea840eca013808d33ce5ad38ad7ee00e3f4e34f3833c35b6326237e51f377b"
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"R9": {
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},
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "54455354204d756c74692d4275796572"
}
}
},
{
"boxId": "2d864732a97ad512a852cef58900985c6416e5329eda274cf5956433f2eeeda3",
"value": 1000000,
"index": 1,
"spendingProof": "16039c7192b95434c439f45cf79950f6517ce495ef57417d4804bf720103804502a444856416cefac45b7c30094bdb39574b0716c3d6ca8b",
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"outputTransactionId": "c203ed9ef7e563d780d34bd0aaff300ef1acfe985aa23d0c9e08db25ce33e289",
"outputIndex": 1,
"outputGlobalIndex": 54264336,
"outputCreatedAt": 1746844,
"outputSettledAt": 1746845,
"ergoTree": "0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bda269,1a4560,...)))}",
"address": "9huKeYQbBnuGcndNCSbxUrRc2sRQNCvfyex8nMorKkEwLcQW4vd",
"assets": [
{
"tokenId": "fbea840eca013808d33ce5ad38ad7ee00e3f4e34f3833c35b6326237e51f377b",
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"amount": 4,
"name": "TEST Multi-Buyer",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
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"outputGlobalIndex": 54263003,
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"outputSettledAt": 1746796,
"ergoTree": "0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bda269,1a4560,...)))}",
"address": "9huKeYQbBnuGcndNCSbxUrRc2sRQNCvfyex8nMorKkEwLcQW4vd",
"assets": [
{
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],
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"R6": {
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"sigmaType": "Coll[SByte]",
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},
"R8": {
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},
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"sigmaType": "Coll[SByte]",
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"renderedValue": "54455354204254432050757420536967555344202437324b"
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"ergoTree": "0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bda269,1a4560,...)))}",
"address": "9huKeYQbBnuGcndNCSbxUrRc2sRQNCvfyex8nMorKkEwLcQW4vd",
"assets": [
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{
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"ergoTree": "0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bda269,1a4560,...)))}",
"address": "9huKeYQbBnuGcndNCSbxUrRc2sRQNCvfyex8nMorKkEwLcQW4vd",
"assets": [
{
"tokenId": "b2da636ee9f1c1c06e22252fa029aa86ea15fbeb623b65d288a41fc68556235a",
"index": 0,
"amount": 2,
"name": "TEST BTC Cash ITM $69K",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297",
"index": 1,
"amount": 29950000,
"name": "rsADA",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "52fe071c4acf4ffdacdeb660e6df06c8f564546e47afc82d64a2b619a39843ce",
"index": 2,
"amount": 3,
"name": "TEST BTC Put SigUSD $72K",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "fa70b45006e7d2235cf5afdbd6a073326fc17beb93ddcbfaff203078715962b7",
"index": 3,
"amount": 4,
"name": "TEST BTC Cash ITM $69K",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "7b990bfd7aa403d4ab4b87f0f911d12291e298ca2aeb1148d4e1b71702cc1c06",
"index": 4,
"amount": 3,
"name": "TEST Gold Call SigUSD",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f69a4cf51572a6c8e10766d727939900fcf9dfe6df09200f4d43e4e17855b51e",
"index": 5,
"amount": 2,
"name": "TEST BTC Cash ITM $69K",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "bd949584b48f25eff5c3069df4d749a7101477a41a0012450f3141d957a06d8f",
"index": 6,
"amount": 10,
"name": "TEST Partial Exercise",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "0aa6a8799619625cee9b84bde37245058d92e9dfa52799ab5e15b48bcf80dc94",
"index": 7,
"amount": 3,
"name": "TEST rsADA Put ITM $0.30",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "b46236ab1dcc25c2d0e06b1d4e0471dda00d52487cce1b3f68b1f3e950df5d91",
"index": 8,
"amount": 2,
"name": "TEST rsADA Call ITM $0.25",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "c8c2aa80ec380f7b3b5afcfa86d00b4adcfda04f0edbd8802f739d359cd0935d",
"index": 9,
"amount": 2,
"name": "TEST BTC Cash ITM $69K",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "008511702663af781652fbf77410a751368225aff1b6c439942d7252b849b7c6",
"index": 10,
"amount": 2,
"name": "TEST BTC Cash ITM $69K",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "8ca74d774585d7114fc5afedd29c5781332126153974aedf59bdd00f271d14ba",
"index": 11,
"amount": 2,
"name": "TEST BTC Cash ITM $69K",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "a55b8735ed1a99e46c2c89f8994aacdf4b1109bdcf682f1e5b34479c6e392669",
"index": 12,
"amount": 1200,
"name": "USE",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "6122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad",
"index": 13,
"amount": 7,
"name": "DexyGold",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "ac99a1eadde51e62cb48b85731e46ef56136a0a2c2c0d035416475f79e736ef0",
"value": 150000000,
"index": 0,
"outputBlockId": "a0572fca9270bb8f8253e852730a68dadb254a03b7e96cfd573736e51e63a85e",
"outputTransactionId": "16ac127b686954c7163ac83517e271083b90f1e79438d8a2fe08236efef46552",
"outputIndex": 0,
"ergoTree": "10040e20ea7b36e294b1a954a80752eac288711728e5b91b0b3c0596548c755665050b88040004000400d804d6017300d602b2a5730100d603b1e4c67202041ad604b1e4c672020511ea02d1ededededededed938cb2db6308a7730200017201938cb2db6308720273030001720193c27202c2a7927203b1e4c6a7041a927204b1e4c6a70511937203720492c17202c1a7e6c672020608e4c6a70608",
"address": "QqJr1n1xDwmVKHreupY52BAX35qjNng6DCjpvB2dUpqTWaBxXtHJvuY5qFYg25xQ8fQ7kFdodBmXqGDAoRcsJHoaTt4MvjCyAz2hJPpG1Br9o3YBwoFvJyufMSjTwbSVGrPKSxPq9f1TBpJuthgw7rMgd6DDwDndMyiQ4M9wnm9FXuup12EzDTZavsJ1D6bPD81eS1iR6ppRNcVyEbAr95kRkry",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1a1520203ef3066a912f35c488487cc2cb94bdb0d30680dab22551c7e6fdbc70dfcc8e207a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b020050322548722d36f094e341f59ed93eb22118b363eb4efe8c461a52c4d93e2c32048132396ebd00831e603c73cf01e01f248dd1966d2cc976caf52ef76f7ac6e3620e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c29700000000000000000000000000206122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad0000",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[203ef3066a912f35c488487cc2cb94bdb0d30680dab22551c7e6fdbc70dfcc8e,7a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b0,050322548722d36f094e341f59ed93eb22118b363eb4efe8c461a52c4d93e2c3,48132396ebd00831e603c73cf01e01f248dd1966d2cc976caf52ef76f7ac6e36,e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297,,,,,,,,,,,,,,6122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad,,]"
},
"R5": {
"serializedValue": "111580a8d6b9078084af5f80a8d6b90780897a80897a00000000000000000000000080a8d6b907fee5030000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1000000000,100000000,1000000000,1000000,1000000,0,0,0,0,0,0,0,0,0,0,0,0,1000000000,31103,0,0]"
},
"R6": {
"serializedValue": "08cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"sigmaType": "SSigmaProp",
"renderedValue": "03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b"
}
}
}
],
"outputs": [
{
"boxId": "e476c1ca4e437e8b4856b8f870db0fa92aed91ee75064725d8aeaa3000fa7ec9",
"transactionId": "51fc2e8a7f769cba634c43a73924683aae8d8f3489133bff70917b262d7043ff",
"blockId": "af6da11c730fddb471341cfa4786567ff58344ffb5ccf342c2465b4d3436a00e",
"value": 61000000,
"index": 0,
"globalIndex": 54264421,
"creationHeight": 1746845,
"settlementHeight": 1746847,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 8\n5: 7\n6: Coll(-22,123,54,-30,-108,-79,-87,84,-88,7,82,-22,-62,-120,113,23,40,-27,-71,27,11,60,5,-106,84,-116,117,86,101,5,11,-120)\n7: 0\n8: Coll(-91,91,-121,53,-19,26,-103,-28,108,44,-119,-8,-103,74,-84,-33,75,17,9,-67,-49,104,47,30,91,52,71,-100,110,57,38,105)\n9: 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)\n10: 10\n11: 4\n12: 6\n13: 1000000\n14: false\n15: 5\n16: 0\n17: 1\n18: 2\n19: 9\n20: 1\n21: 1\n22: 1\n23: 0\n24: 3\n25: 5\n26: 1\n27: 0\n28: 0\n29: 1\n30: 2\n31: 1\n32: 3\n33: 0\n34: 1000000\n35: 0\n36: 0\n37: 0\n38: 17\n39: 0\n40: 0\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 0\n47: 1000\n48: 100\n49: 1000\n50: 0\n51: 100\n52: 0\n53: 2\n54: 0\n55: 17\n56: 1\n57: 2\n58: 17\n59: 0\n60: 17\n61: 1000000\n62: 0\n63: 3\n64: 2000000\n65: 1\n66: 1\n67: 1\n68: 1\n69: 2\n70: 1\n71: 1000000\n72: 0\n73: 1\n74: 2\n75: 1\n76: 0\n77: false\n78: 1\n79: 3\n80: 1000000\n81: 1\n82: 1000000\n83: 1\n84: 1\n85: false\n86: 0\n87: 0\n88: 0\n89: 0\n90: 0\n91: 1000000\n92: 1000000\n93: 0\n94: 0\n95: 1000\n96: 0\n97: 17\n98: 0\n99: 17\n100: 2\n101: 1\n102: 2\n103: 0\n104: true\n105: 1\n106: 2\n107: 0\n108: true\n109: false\n110: 1\n111: 0\n112: 1\n113: 0\n114: 0\n115: 0\n116: 0\n117: 1000000\n118: 0\n119: Coll(49,-126,103,79,7,-37,-71,-115,105,109,56,-19,-91,62,99,-21,59,-11,-2,87,15,113,-34,-24,94,-71,84,-42,-49,-112,59,-70)\n120: 0\n121: 0\n122: 0\n123: true\n124: false\n125: 2\n126: false",
"ergoTreeScript": "{\n val coll1 = SELF.R9[Coll[Coll[Byte]]].get\n val prop2 = proveDlog(decodePoint(coll1(placeholder[Int](0))))\n val coll3 = SELF.tokens\n val tuple4 = (Coll[Byte](), placeholder[Long](1))\n val tuple5 = coll3.getOrElse(placeholder[Int](2), tuple4)\n val coll6 = tuple5._1\n val coll7 = SELF.R7[Coll[Byte]].get\n val bool8 = coll6 == coll7\n val bool9 = !bool8\n val box10 = OUTPUTS(placeholder[Int](3))\n val coll11 = box10.propositionBytes\n val coll12 = prop2.propBytes\n val coll13 = SELF.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](4))\n val l15 = coll13(placeholder[Int](5))\n val coll16 = placeholder[Coll[Byte]](6)\n val l17 = coll13(placeholder[Int](7))\n val coll18 = placeholder[Coll[Byte]](8)\n val coll19 = placeholder[Coll[Byte]](9)\n val l20 = coll13(placeholder[Int](10))\n val l21 = coll13(placeholder[Int](11))\n val l22 = coll13(placeholder[Int](12))\n val l23 = l22 + placeholder[Long](13)\n val coll24 = SELF.R5[Coll[Byte]].get\n val bool25 = if (coll11 == SELF.propositionBytes) {\n (\n (\n (((box10.value >= l23) && (box10.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box10.R5[Coll[Byte]].get == coll24)) && (\n box10.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get\n )\n ) && (box10.R8[Coll[Long]].get == coll13)\n ) && (box10.R9[Coll[Coll[Byte]]].get == coll1)\n } else { placeholder[Boolean](14) }\n val coll26 = SELF.id\n val l27 = coll13(placeholder[Int](15))\n val coll28 = box10.tokens\n val tuple29 = coll28.getOrElse(placeholder[Int](16), tuple4)\n val coll30 = tuple29._1\n val tuple31 = coll28.getOrElse(placeholder[Int](17), tuple4)\n val l32 = tuple5._2\n val l33 = coll13(placeholder[Int](18))\n val l34 = tuple29._2\n val coll35 = tuple31._1\n val l36 = coll13(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool8 && (l32 == placeholder[Long](21))\n val tuple40 = coll3.getOrElse(placeholder[Int](22), tuple4)\n val tuple41 = coll38.getOrElse(placeholder[Int](23), tuple4)\n val l42 = HEIGHT.toLong\n val l43 = coll13(placeholder[Int](24))\n val l44 = l43 + placeholder[Long](25)\n val bool45 = if (coll13(placeholder[Int](26)) == placeholder[Long](27)) { (bool39 && (l42 >= l43)) && (l42 <= l44) } else { bool39 && (l42 <= l44) }\n val l46 = INPUTS.fold(placeholder[Long](28), {(tuple46: (Long, Box)) =>\n val box48 = tuple46._2\n val l49 = tuple46._1\n if (box48.id != coll26) { box48.tokens.fold(l49, {(tuple50: (Long, (Coll[Byte], Long))) =>\n val tuple52 = tuple50._2\n val l53 = tuple50._1\n if (tuple52._1 == coll7) { l53 + tuple52._2 } else { l53 }\n }) } else { l49 }\n })\n val bool47 = ((bool25 && (box10.R7[Coll[Byte]].get == coll7)) && \n val coll47 = coll30\n coll47 == coll6\n ) && (l34 == placeholder[Long](29))\n val l48 = tuple31._2\n prop2 && sigmaProp((bool9 && (OUTPUTS.size == placeholder[Int](30))) && (coll11 == coll12)) || sigmaProp(\n (((if ((bool9 && (INPUTS.size == placeholder[Int](31))) && (OUTPUTS.size == placeholder[Int](32))) {(\n val bool49 = l14 == placeholder[Long](33)\n val l50 = l21 * l20 / placeholder[Long](34)\n val bool51 = l50 > placeholder[Long](35)\n ((((((((((if (bool49) {(\n val box52 = CONTEXT.dataInputs(placeholder[Int](36))\n val i53 = l15.toInt\n val l54 = box52.R5[Coll[Long]].get(i53)\n val bool55 = box52.tokens(placeholder[Int](37))._1 == coll16\n val coll56 = box52.R4[Coll[Coll[Byte]]].get(i53)\n if (l15 == placeholder[Long](38)) { bool55 && (l54 > placeholder[Long](39)) } else { if (l17 == placeholder[Long](40)) { ((bool55 && (coll56.size > placeholder[Int](41))) && (l54 > placeholder[Long](42))) && (coll3(placeholder[Int](43))._1 == coll56) } else { (bool55 && (coll56.size > placeholder[Int](44))) && (l54 > placeholder[Long](45)) } }\n )} else {(\n val coll52 = coll3(placeholder[Int](46))._1\n (coll52 == coll18) || (coll52 == coll19)\n )} && if (bool49) { (l20 == placeholder[Long](47)) || (l20 == placeholder[Long](48)) } else { ((l20 == placeholder[Long](49)) && (coll3(placeholder[Int](50))._1 == coll18)) || ((l20 == placeholder[Long](51)) && (coll3(placeholder[Int](52))._1 == coll19)) }) && bool51) && bool25) && (box10.R7[Coll[Byte]].get == coll26)) && (box10.value == SELF.value - l22 - l27)) && (box10.value >= placeholder[Long](53) * l23)) && (coll30 == coll26)) && \n val bool52 = l17 == placeholder[Long](54)\n ((((((((bool52 && bool49) && (l15 != placeholder[Long](55))) && \n val coll53 = coll35\n coll53 == coll24\n ) && (tuple31 == tuple5)) && (l34 == l32 / l33 + placeholder[Long](56))) && (coll28.size == placeholder[Int](57))) || (((bool52 && bool49) && (l15 == placeholder[Long](58))) && \n val l53 = l33 * CONTEXT.dataInputs(placeholder[Int](59)).R5[Coll[Long]].get(placeholder[Int](60)) / placeholder[Long](61)\n val l54 = SELF.value\n (((l53 > placeholder[Long](62)) && (l34 == l54 - placeholder[Long](63) * l22 - l27 - placeholder[Long](64) / l53 + placeholder[Long](65))) && (coll28.size == placeholder[Int](66))) && (box10.value >= l54 - l22 - l27)\n )) || (((((((l17 == placeholder[Long](67)) && bool49) && (coll35 == coll24)) && (tuple31 == tuple5)) && bool51) && (l34 == l32 / l50 + placeholder[Long](68))) && (coll28.size == placeholder[Int](69)))) || ((l14 == placeholder[Long](70)) && \n val l53 = l36 * l20 / placeholder[Long](71)\n ((((l53 > placeholder[Long](72)) && (coll35 == coll24)) && (tuple31 == tuple5)) && (l34 == l32 / l53 + placeholder[Long](73))) && (coll28.size == placeholder[Int](74))\n )\n ) && (box37.propositionBytes == coll1(placeholder[Int](75)))) && (coll38.size == placeholder[Int](76))) && (box37.value >= l27)\n )} else { placeholder[Boolean](77) } || if (((bool8 && (!bool39)) && (INPUTS.size == placeholder[Int](78))) && (OUTPUTS.size == placeholder[Int](79))) { ((((((((((box10.value == SELF.value - l22 - placeholder[Long](80)) && bool25) && (box10.R7[Coll[Byte]].get == coll7)) && (coll30 == coll6)) && (l34 == placeholder[Long](81))) && (tuple31 == tuple40)) && (box37.propositionBytes == coll12)) && (box37.value == placeholder[Long](82))) && (coll38.size == placeholder[Int](83))) && (tuple41._1 == coll6)) && (tuple41._2 == l32 - placeholder[Long](84)) } else { placeholder[Boolean](85) }) || if ((bool45 && (l14 == placeholder[Long](86))) && (l46 > placeholder[Long](87))) {(\n val box49 = CONTEXT.dataInputs(placeholder[Int](88))\n val i50 = l15.toInt\n val l51 = box49.R5[Coll[Long]].get(i50)\n val bool52 = l51 > placeholder[Long](89)\n val bool53 = box49.tokens(placeholder[Int](90))._1 == coll16\n val l54 = l33 * l51 / placeholder[Long](91)\n val l55 = l21 * l20 / placeholder[Long](92)\n val bool56 = (l54 > placeholder[Long](93)) && (l55 > placeholder[Long](94))\n val l57 = l54 * l46\n val coll58 = if (l20 == placeholder[Long](95)) { coll18 } else { coll19 }\n val l59 = l55 * l46\n val coll60 = box49.R4[Coll[Coll[Byte]]].get(i50)\n val bool61 = (coll60.size > placeholder[Int](96)) || (l15 == placeholder[Long](97))\n if (l17 == placeholder[Long](98)) { if (l15 == placeholder[Long](99)) {(\n val box62 = OUTPUTS(placeholder[Int](100))\n (((((bool53 && bool52) && bool56) && (box37.value >= l57)) && ((box62.propositionBytes == coll12) && box62.tokens.exists({(tuple63: (Coll[Byte], Long)) => (tuple63._1 == coll58) && (tuple63._2 >= l59) }))) && bool47) && (box10.value >= SELF.value - l57 - l22)\n )} else {(\n val tuple62 = coll3(placeholder[Int](101))\n val box63 = OUTPUTS(placeholder[Int](102))\n (((((((((bool53 && bool61) && bool52) && bool56) && (tuple62._1 == coll60)) && coll38.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll60) && (tuple64._2 >= l57) })) && ((box63.propositionBytes == coll12) && box63.tokens.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll58) && (tuple64._2 >= l59) }))) && if (l48 > placeholder[Long](103)) { coll35 == coll60 } else { placeholder[Boolean](104) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple62._2 - l57)\n )} } else {(\n val tuple62 = coll3(placeholder[Int](105))\n val coll63 = tuple62._1\n val box64 = OUTPUTS(placeholder[Int](106))\n (((((((((bool53 && bool61) && bool52) && bool56) && ((coll63 == coll18) || (coll63 == coll19))) && coll38.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll63) && (tuple65._2 >= l59) })) && ((box64.propositionBytes == coll12) && box64.tokens.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll60) && (tuple65._2 >= l57) }))) && if (l48 > placeholder[Long](107)) { coll35 == coll63 } else { placeholder[Boolean](108) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple62._2 - l59)\n )}\n )} else { placeholder[Boolean](109) }) || if ((bool45 && (l14 == placeholder[Long](110))) && (l46 > placeholder[Long](111))) {(\n val tuple49 = coll3(placeholder[Int](112))\n val coll50 = tuple49._1\n val box51 = CONTEXT.dataInputs(placeholder[Int](113))\n val l52 = box51.R8[Coll[Long]].get(l15.toInt)\n val l53 = if (l17 == placeholder[Long](114)) { if (l52 > l21) {(\n val l53 = l52 - l21\n if (l53 > l36) { l36 } else { l53 }\n )} else { placeholder[Long](115) } } else { if (l52 < l21) {(\n val l53 = l21 - l52\n if (l53 > l36) { l36 } else { l53 }\n )} else { placeholder[Long](116) } }\n val l54 = l53 * l20 / placeholder[Long](117)\n val l55 = l54 * l46\n (((((((((coll50 == coll18) || (coll50 == coll19)) && (box51.tokens(placeholder[Int](118))._1 == placeholder[Coll[Byte]](119))) && (l53 > placeholder[Long](120))) && (l54 > placeholder[Long](121))) && coll38.exists({(tuple56: (Coll[Byte], Long)) => (tuple56._1 == coll50) && (tuple56._2 >= l55) })) && if (l48 > placeholder[Long](122)) { coll35 == coll50 } else { placeholder[Boolean](123) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple49._2 - l55)\n )} else { placeholder[Boolean](124) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](125)) && (coll11 == coll12)) && (box10.value >= SELF.value - l22)) && (coll30 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](126) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "fbea840eca013808d33ce5ad38ad7ee00e3f4e34f3833c35b6326237e51f377b",
"index": 0,
"amount": 1,
"name": "TEST Multi-Buyer",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0e0139",
"sigmaType": "Coll[SByte]",
"renderedValue": "39"
},
"R8": {
"serializedValue": "110b0002a09c01989fd50180b51880897a80c78c02220000d00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,10000,1746892,200000,1000000,2200000,17,0,0,1000]"
},
"R7": {
"serializedValue": "0e20fbea840eca013808d33ce5ad38ad7ee00e3f4e34f3833c35b6326237e51f377b",
"sigmaType": "Coll[SByte]",
"renderedValue": "fbea840eca013808d33ce5ad38ad7ee00e3f4e34f3833c35b6326237e51f377b"
},
"R9": {
"serializedValue": "1a022103bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b240008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b,0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b]"
},
"R4": {
"serializedValue": "0e1054455354204d756c74692d4275796572",
"sigmaType": "Coll[SByte]",
"renderedValue": "54455354204d756c74692d4275796572"
}
},
"spentTransactionId": "9433834d083dc43b71ba98707d15273f8104a992f09ab60b0f96c97793fe45e5",
"mainChain": true
},
{
"boxId": "f6ddd0962a7b9fd97b1ae441d0b00e0bd89dd8bbc52cc5f273ed1e35f316a370",
"transactionId": "51fc2e8a7f769cba634c43a73924683aae8d8f3489133bff70917b262d7043ff",
"blockId": "af6da11c730fddb471341cfa4786567ff58344ffb5ccf342c2465b4d3436a00e",
"value": 40000000,
"index": 1,
"globalIndex": 54264422,
"creationHeight": 1746845,
"settlementHeight": 1746847,
"ergoTree": "0008cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bda269,1a4560,...)))}",
"address": "9huKeYQbBnuGcndNCSbxUrRc2sRQNCvfyex8nMorKkEwLcQW4vd",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "03ec25fd1402637c5a4fb8c9f482c5b1d5b4780de42700d186952eca9ee8be00",
"mainChain": true
},
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