Transaction
ID: dc701ecbae...7c29
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.07 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
212.31 ERG
Tokens:
Loading assets...
Outputs (14)
Unspent
Unspent
Unspent
Unspent
Unspent
Unspent
Unspent
Unspent
Unspent
Unspent
Unspent
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
212.34 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 784,863
Total coins transferred: 212.39 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000184 ERG
Raw Transaction Data
{
"id": "dc701ecbaea5af249cc8c1959cfc55b306badfe8d744876ae701c6c194957c29",
"blockId": "7c40c84ca5d23a567a63c8b4fad2b791a70bc6973d00f4ec4b5ab4a17c6836d0",
"inclusionHeight": 987980,
"timestamp": 1682166929651,
"index": 8,
"globalIndex": 5086524,
"numConfirmations": 784863,
"inputs": [
{
"boxId": "55c942f85791574c070e104dc3d09adadacdfd3c199cbb51772f90d5571ec3aa",
"value": 11000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "fe30028ef7f8ce7c75af2016869d91d2ed888b121ede3c9236d8c7a6f2af2422",
"outputTransactionId": "34b2490351a1e0b132ec93fb3c2502673c2dc2f26c6ead2b35cd19e80cc77135",
"outputIndex": 0,
"outputGlobalIndex": 28496042,
"outputCreatedAt": 987915,
"outputSettledAt": 987919,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-67,102,62,43,69,125,66,119,20,61,66,-32,-38,-24,33,73,-18,15,41,-119,-44,14,-39,-97,67,86,78,-58,-10,-55,-33,-1)\n3: 1\n4: 0\n5: Coll(101,33,76,-91,63,-65,9,-64,-121,93,113,-10,127,40,-96,71,26,77,109,79,102,-61,-118,-28,123,106,65,126,100,95,104,-3)\n6: 7200\n7: Coll(-93,87,-80,5,86,-23,-23,60,104,-34,26,73,-30,-7,-41,-60,-110,93,-91,-62,118,103,2,-20,73,-79,-91,14,88,40,23,19)",
"ergoTreeScript": "{\n val coll1 = SELF.R4[Coll[Coll[Byte]]].get\n val i2 = coll1.size\n val coll3 = OUTPUTS.slice(placeholder[Int](0), i2)\n val coll4 = OUTPUTS(placeholder[Int](1)).propositionBytes\n val coll5 = blake2b256(coll4)\n sigmaProp(allOf(Coll[Boolean](i2 == coll3.size, coll1.zip(coll3).forall({(tuple6: (Coll[Byte], Box)) =>\n val box8 = tuple6._2\n (Coll[Coll[Byte]](tuple6._1) == box8.R4[Coll[Coll[Byte]]].get) && (box8.propositionBytes == coll4)\n }), if (coll5 == placeholder[Coll[Byte]](2)) { allOf(Coll[Boolean](INPUTS(placeholder[Int](3)).tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), HEIGHT - placeholder[Int](6) >= SELF.creationInfo._1)) } else { allOf(Coll[Boolean](INPUTS.exists({(box6: Box) => blake2b256(box6.propositionBytes) == placeholder[Coll[Byte]](7) }), coll5 == SELF.R6[Coll[Byte]].get)) })))\n}",
"address": "21oSXpSmAC6qpaSpnMff4uYgpsaCjJ6q8tnvnE3MGp5QjNrtqGSHjip4VcuDGGeuMVg1RH9dxfWhT4LwJZrnwBvTkztYv4wLTXRz8Cwr9ENigonokQBnQiT7d5GDyzuedPdYVKGezdqDWrL56BWRe9NZgP56x5r7kxw9koHjQFAJ9RJADQrUKyKnvyk9jHmK1auNUik23CMK2SxedeWg1HkEYhrdvucvfyJ6hJZqbMbhuh6uYY5XPXLfJuz6kNNnWXb7pv4FtoNZXnRbx4uZcVjYGLV88pETGTyCTpjK8e1VHxBTyY2zPF4efLnYxkvrG8YT31nn5ctrFtKtbDG5etZeomMT1f73aLS7Fu42cxhzvRouxL",
"assets": [
{
"tokenId": "9410db5b39388c6b515160e7248346d7ec63d5457292326da12a26cc02efb526",
"index": 0,
"amount": 10,
"name": "Ergo-RWT.V-test",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[ba094ca44078a94c780eb7df8e0e8ddcefda1d819bc026250c327b5f044fc100,e8d2e63d683f57b1dc19bd554a316954703b74b1ebf7459f8b9cb8316dc6e6ba,97a2dabcd974d69a07c3a03e20d05a36d13b986ffca5670302997484dd87e247,0e83836f818a16766ac7490c5eee7abdc9357e6bb955641ff8ac56412bf576d0,549f37b65bf1c38e24132eeebe9053e8c1e8798a622cd0b3eccda1944ce9aad1,7dc9b5fd90c4343d48baddc8a7df8b005dd25a2765dadcabd6bfdcc337bcc292,0ea77346ecd826701113ef3596670f85ec0d4a000d37a06a762ba14623f360f3,35f401c431c3adcd4675177be89cc05c70a45de782e93dc226c545e38e37b95c,307f6f54ca9bd07e1d979beb6d2a35a19ef03339cad45d3f7a3f9aba327799ea,5cea78cd9e83ad6de5ae2b4a44494507dd74a8c13223621edfc553b902d5bf7e]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[35643131363363326638316334656433646366356537303935313463383937633438343166356438366235336133373137306131633138376338313363326133,6572676f,63617264616e6f,39694e57395a3548466a33716f3335747777446241574d75747365647766627378484e713175665358676d3578477266554b58,61646472317178686d687478796b35777266703678617a7336343765743861303575636c3635347573706e796c336534636e307468793072377435337570616b7173667039616a7137773876753838656d706d61753379737539736d7077326171323635307970,00000000042c1d80,0000000002faf080,0000000000013880,657267,6173736574316a7935713561307670737475747135713664386367646d72643471753579656663646e6a677a,37633734366331396237313438656461336238303535626162663265326130323261333733393232393634633237366363393361383030373636393533643830,00000000000f12ec]"
},
"R6": {
"serializedValue": "0e20fdd14a1fc1c52cdddd322f6cd2e9c6afa050691f0e48784570edd24d4dd2ca20",
"sigmaType": "Coll[SByte]",
"renderedValue": "fdd14a1fc1c52cdddd322f6cd2e9c6afa050691f0e48784570edd24d4dd2ca20"
}
}
},
{
"boxId": "5a57624bc6c54f65ed8fcff6cd595bd6087b774f4effc48ef49be7ee32e03571",
"value": 70000000,
"index": 1,
"spendingProof": "0aa9d11fc6920729b6d60937177b85ba8fc204f1a06ae46d6d4236dc7e2d83b5e043f2f4fadd93834dc4211e03cf5a60e99b28196cf10a33effef1b7a28a1b2b505eeb0c57186b663c9d20d5a5ea8c8d483bee1e52d3d8a01e69094c482c6d8f5d9165b2695bfcd413f9635f03f20c9a8e4065c969bc0b08b276148930a57ddf0c0a5d17e5e0c9a6b574972479c7d597e2e8289c5af215750c4f902cd4ae58ed35dcd2366360e2501d22e1a7850ca5dfde8d3e899ce6241e13530f43ce2a42b391fdf50301bded263d8bdb1143ff48c12cdd27d86c40a3c41578a2c9897ca37a1752c95467c2a558c8394203f4767a2f36f792fd04a9f171c5bf364915c1ba80edb073cbf1bf0777fc97ebdf570cf859a8dce5f67b2bf1319024439aeff0a84e4c4effc16433d6e59a045cafe8d08ac0da81e8ed4fc1bccef387a78269bbe905e173c2152fa652db7151eebf9f128715fb0913919a1e059e71bc27e86626f878f974a4d45c2d0dd671e1b159d48223297c73b72595eb3e7a26395e33bbd9212703c6a8178e18d4b41c73e5ffe3b8b6e26dc407fbae45ff0fdc68bd55d9de73a0",
"outputBlockId": "7c746c19b7148eda3b8055babf2e2a022a373922964c276cc93a800766953d80",
"outputTransactionId": "5d1163c2f81c4ed3dcf5e709514c897c4841f5d86b53a37170a1c187c813c2a3",
"outputIndex": 0,
"outputGlobalIndex": 28495087,
"outputCreatedAt": 987881,
"outputSettledAt": 987884,
"ergoTree": "100304000e20b039e4445337697deaad703fc8d1fcb129c4577e8673394fa2403e54d484eeda0400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-80,57,-28,68,83,55,105,125,-22,-83,112,63,-56,-47,-4,-79,41,-60,87,126,-122,115,57,79,-94,64,62,84,-44,-124,-18,-38)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LSRBnqR67yQfE5ZFAez3ySUzwouks1yjB696YSzRZ3D9BdFDntw4DAfp7yXKXykxAYE9sSBXmv9PRH1znnAWZAwzb6NDK4pn1S7LTU3omgYnuabg7VkiFxqqdY3bqw7UXeHB4",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1a050763617264616e6f6761646472317178686d687478796b35777266703678617a7336343765743861303575636c3635347573706e796c336534636e307468793072377435337570616b7173667039616a7137773876753838656d706d61753379737539736d70773261713236353079700538303030300835303030303030303339694e57395a3548466a33716f3335747777446241574d75747365647766627378484e713175665358676d3578477266554b58",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[63617264616e6f,61646472317178686d687478796b35777266703678617a7336343765743861303575636c3635347573706e796c336534636e307468793072377435337570616b7173667039616a7137773876753838656d706d61753379737539736d7077326171323635307970,3830303030,3530303030303030,39694e57395a3548466a33716f3335747777446241574d75747365647766627378484e713175665358676d3578477266554b58]"
}
}
},
{
"boxId": "344467f00f2f9b87b09ab54973008e0391ca296517e89eab2e083c7218419cb4",
"value": 212307486360,
"index": 2,
"spendingProof": "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",
"outputBlockId": "5d05c6a2d2e9f526bf7c3dfd58841ddacd557f8a88e15435615bd39f5f85ff9b",
"outputTransactionId": "28e1cbc78b5847d57278169cf685eaef37c10ac7f18d26d07b0c5539c6d539a1",
"outputIndex": 12,
"outputGlobalIndex": 28498611,
"outputCreatedAt": 987965,
"outputSettledAt": 987974,
"ergoTree": "100304000e20b039e4445337697deaad703fc8d1fcb129c4577e8673394fa2403e54d484eeda0400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-80,57,-28,68,83,55,105,125,-22,-83,112,63,-56,-47,-4,-79,41,-60,87,126,-122,115,57,79,-94,64,62,84,-44,-124,-18,-38)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LSRBnqR67yQfE5ZFAez3ySUzwouks1yjB696YSzRZ3D9BdFDntw4DAfp7yXKXykxAYE9sSBXmv9PRH1znnAWZAwzb6NDK4pn1S7LTU3omgYnuabg7VkiFxqqdY3bqw7UXeHB4",
"assets": [
{
"tokenId": "4ed6449240d166b0e44c529b5bf06d210796473d3811b9aa0e15329599164c24",
"index": 0,
"amount": 44999999981000000,
"name": "RST-ADA.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a1143e81c5ab485a807e6f0f76af1dd70cc5359b29e0b1229d0edfe490d33b67",
"index": 1,
"amount": 4831963150,
"name": "Ergo-Token.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "c59e86ef9d0280de582d6266add18fca339a77dfb321268e83033fe47101dc4d",
"index": 2,
"amount": 499999081615899,
"name": "RST-Cardano-Token.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "51c1745883a62db6cf47f5765bd695317a01e54bcaaaeaa4aab0b517d2f46a24",
"index": 3,
"amount": 99999999979886460,
"name": "RSN.V-test",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "6eccf30dc9e6d40e20f8dddc3d66e7ee45c82216906a2bacf14be9da8a811309",
"value": 1100000,
"index": 0,
"outputBlockId": "e9281ffbb4be4b17869a79f353c926eb9a8db781db891b16f8ab6bbb226ef0ff",
"outputTransactionId": "2d6baff61607166b03da7c68eec2d3ea4611ff88cbf36d964f648f64f8c2cfb8",
"outputIndex": 0,
"ergoTree": "100504000400040004000402d802d601c2a7d602b2a5730000ea02d196830301937201c2b2a473010093c272027201938cb2db63087202730200018cb2db6308a77303000198b2e4c6a70510730400ade4c6a7041ad901030ecdee7203",
"address": "MZ4DGXjbMTDYv4wnEPCSzRGp3infV4oBqQvJhnnePTb61wYrGaS2oiNAbesgJphKS3v5tA3cqaEXUdgRP5EsKBihXwSSogs4RNVhhsYyQiYHoWNo3jB7Fm2DDQSVLJZCf41sd",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[03c236922914cf80be4b642b3ea02f532ceb120a82b7bc5b75a8c2b7dc70810a27,02b1d6b33c5ef442fa140d52352cab3e80780e98a44bcf6826604f100dbe2cbec8,0217b8b16c47f83c6e96324f4d65434cd77aca1ab969878ba8293b87001c4f216f,024df46a0f95903d15cc8c4f390bb3d0f97dee85273591a88575206baf2d54812e,03aa26adb6a56132f52c0919a351b738beee0d2a240d6b5a82eff27a0f662f3459,02d64bd38b103af945c5786dfbd63577779f49e7166e69f622dc5c243dcbbdbab9,024f0556828a51b54a2b17bf9d4cc4c7fd9faa3226513193ae0aeaf9075bad4aca,02a8b0cc627e16301030b1a74fc33d49dd364a2b818d5d25e02b4d9e3bfc1f4aac,03380c129ffb41ccc52dd58a128082ac381bb449ef67d230255eea284255998524,023605f5625c0f1099c5966a58a9291d7a546d432faeb99d88a99fa6b745b1fd31]"
},
"R5": {
"serializedValue": "10020e10",
"sigmaType": "Coll[SInt]",
"renderedValue": "[7,8]"
}
}
}
],
"outputs": [
{
"boxId": "5bc238fe880acfe18d0bb8786a49a0fae452a8499fd7a8d286d4d9ed624166d2",
"transactionId": "dc701ecbaea5af249cc8c1959cfc55b306badfe8d744876ae701c6c194957c29",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[Coll[SByte]]",
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"type": "EIP-004"
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"sigmaType": "Coll[Coll[SByte]]",
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"type": "EIP-004"
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[0ea77346ecd826701113ef3596670f85ec0d4a000d37a06a762ba14623f360f3]"
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"index": 7,
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"creationHeight": 987974,
"settlementHeight": 987980,
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[35f401c431c3adcd4675177be89cc05c70a45de782e93dc226c545e38e37b95c]"
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"spentTransactionId": null,
"mainChain": true
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{
"boxId": "a49d5a1ed0262836b6bb35fe0701b72d378d75b4bbc8f0cde313950fdc23ae72",
"transactionId": "dc701ecbaea5af249cc8c1959cfc55b306badfe8d744876ae701c6c194957c29",
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"value": 300000,
"index": 8,
"globalIndex": 28498707,
"creationHeight": 987974,
"settlementHeight": 987980,
"ergoTree": "10130400040004040400040204000e204b1e5bcfbd6763b9cea8411841213611258fabed16293af6aa8cd8200b7e12860404040004000400010104020400040004000e20c2eeb21a772554cc9733586df12f27d2f444f50e623c1f57cf89c09dc5097c5505020101d807d601b2a5730000d6028cb2db6308a773010001d603aeb5b4a57302b1a5d901036391b1db630872037303d9010363aedb63087203d901054d0e938c7205017202d604e4c6a7041ad605b2a5730400d606db63087205d607ae7206d901074d0e938c720701720295938cb2db63087201730500017306d196830301ef7203938cb2db6308b2a473070073080001b2720473090095720796830201938cb27206730a0001720293c27205c2a7730bd801d608c2a7d196830501ef720393c27201720893e4c67201041a7204938cb2db6308b2a4730c00730d0001b27204730e00957207d801d609b27206730f0096830701938c720901720293cbc272057310e6c67205051ae6c67205060e93e4c67205070ecb720893e4c67205041a7204938c72090273117312",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"type": "EIP-004"
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"sigmaType": "Coll[Coll[SByte]]",
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"globalIndex": 28498709,
"creationHeight": 987974,
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"ergoTree": "0008cd02d0b75bc997751195d143671cc10e8a590f25b987f2b2dd0d99cc5f48c6966d3d",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d0b75b,1b1e24,...)))}",
"address": "9g6ytenZVgR3RXYqXUG3vRcXLhmd12VtUKCuecFqL1P18axCErM",
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"sigmaType": "Coll[Coll[SByte]]",
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"index": 11,
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"ergoTree": "0008cd03cc76f1074a4477cd378329c4e902ee6145add72e9c26c82b4f2255e768d48811",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(cc76f1,d4ffcd,...)))}",
"address": "9i1rTxaZpLprUkVHpY4YNyooksLuouiKqZ2v1J5nf8xFTXBCVcB",
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"mainChain": true
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{
"boxId": "97fe7c5e1269fb60c258b895857722d2f986a41f471f5c7829ce855a4fe06c0c",
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"ergoTree": "100304000e20b039e4445337697deaad703fc8d1fcb129c4577e8673394fa2403e54d484eeda0400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-80,57,-28,68,83,55,105,125,-22,-83,112,63,-56,-47,-4,-79,41,-60,87,126,-122,115,57,79,-94,64,62,84,-44,-124,-18,-38)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LSRBnqR67yQfE5ZFAez3ySUzwouks1yjB696YSzRZ3D9BdFDntw4DAfp7yXKXykxAYE9sSBXmv9PRH1znnAWZAwzb6NDK4pn1S7LTU3omgYnuabg7VkiFxqqdY3bqw7UXeHB4",
"assets": [
{
"tokenId": "4ed6449240d166b0e44c529b5bf06d210796473d3811b9aa0e15329599164c24",
"index": 0,
"amount": 44999999981000000,
"name": "RST-ADA.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a1143e81c5ab485a807e6f0f76af1dd70cc5359b29e0b1229d0edfe490d33b67",
"index": 1,
"amount": 4831963150,
"name": "Ergo-Token.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "c59e86ef9d0280de582d6266add18fca339a77dfb321268e83033fe47101dc4d",
"index": 2,
"amount": 499999081615899,
"name": "RST-Cardano-Token.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "51c1745883a62db6cf47f5765bd695317a01e54bcaaaeaa4aab0b517d2f46a24",
"index": 3,
"amount": 99999999979883970,
"name": "RSN.V-test",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "2ef49dfd91a96415b447ac262a028dced520fec98d2ab36249998a434bf085a8",
"mainChain": true
},
{
"boxId": "2ab4155b08d4c01aaec43e8a38f67bea12dbf6d58e51b8f4527b25f90d0d295a",
"transactionId": "dc701ecbaea5af249cc8c1959cfc55b306badfe8d744876ae701c6c194957c29",
"blockId": "7c40c84ca5d23a567a63c8b4fad2b791a70bc6973d00f4ec4b5ab4a17c6836d0",
"value": 1100000,
"index": 13,
"globalIndex": 28498712,
"creationHeight": 987974,
"settlementHeight": 987980,
"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "0514fc5e06ecade2d628d20861e04e19dac90523f01578c0ac080a1037a9468a",
"mainChain": true
}
],
"size": 5975,
"isUnconfirmed": false
}