Transaction
ID: 2356b8255e...c8e5
Inputs (56)
Spent
Address:
Output transaction:
Settlement height:
Value:
16.49 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
33 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.874258 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.06158842 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0001 ERG
Tokens:
24.04
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0001 ERG
Tokens:
4
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0001 ERG
Tokens:
650
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0004 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0004 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0001 ERG
Tokens:
11.36
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
45.45
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
765
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
2,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
118.53
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0004 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0004 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
419.79
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
5,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.05 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.05 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.05 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.05 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.05 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.05 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
5.58 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
16.24 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
22.52 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00025 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
16.5 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.80665 ERG
Tokens:
0
Spent
Address:
Output transaction:
Settlement height:
Value:
888.66 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
800 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
201.05 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 295,678
Total coins transferred: 1,001.05 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000119 ERG
Raw Transaction Data
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"ergoTree": "0008cd036a496ea24cd4ad8465166161832ff49a98a9033956f0ccee63aade73b53c97d9",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6a496e,ce0996,...)))}",
"address": "9hGceS9rTZDDmsnioJGWykfUAzk8ZbCuuadNLvoeG7hN9bM3kNP",
"assets": [
{
"tokenId": "59ee24951ce668f0ed32bdb2e2e5731b6c36128748a3b23c28407c5f8ccbf0f6",
"index": 0,
"amount": 2432998,
"name": "WALRUS",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "081409b82f8acbc751bd5e46d949a46650b537786ecff534659760a56932b8e2",
"index": 1,
"amount": 1,
"name": "Emberrmu",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b",
"index": 2,
"amount": 1000000,
"name": "RSN",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "978198f2ec92375a44678ad7c5dddeb2e7372373fe32f98e7bd32480b8456654",
"index": 3,
"amount": 1,
"name": "ErgoLlama #044",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "c5e1c1dffeac6488383b847a4beb30d0b00edba536c2481ef07b07e09f85afec",
"index": 4,
"amount": 1,
"name": "Bearish Rambo",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fcfca7654fb0da57ecf9a3f489bcbeb1d43b56dce7e73b352f7bc6f2561d2a1b",
"index": 5,
"amount": 68396153000,
"name": "ErgOne",
"decimals": 8,
"type": "EIP-004"
},
{
"tokenId": "ba553573f83c61be880d79db0f4068177fa75ab7c250ce3543f7e7aeb471a9d2",
"index": 6,
"amount": 10000000,
"name": "$BASS",
"decimals": 7,
"type": "EIP-004"
},
{
"tokenId": "57cc99dec63e15396491b2ccfd56d1e752963394eb3478abf4ce0bf0707b83bb",
"index": 7,
"amount": 1,
"name": "Adventurer #016",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "b93a62887f5ace280a8ea3c0238aa957b2ec43797f8afc4dcfc3f4008f3985d8",
"index": 8,
"amount": 1,
"name": "Vector Minimalism. Sisyphus #2",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "007fd64d1ee54d78dd269c8930a38286caa28d3f29d27cadcb796418ab15c283",
"index": 9,
"amount": 5544472453,
"name": "EXLE",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "92e848f2a06b68f690b5650d333919c1ebb36346e7795d9746f886ab5864833c",
"index": 10,
"amount": 1118033989,
"name": "Ergo_59ee2495_LP",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "dfb145d72277f0bfee4edf8bd3980e302d6f6170f65ed048795c8501e88e719d",
"index": 11,
"amount": 1,
"name": "Stoxionne",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "91289d5cefb9d78e3ea248d4e9c5b0e3c3de54f64bfae85c0070580961995262",
"index": 12,
"amount": 1000,
"name": "PEPERG",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "b8164ef79e0e1bbcbe1bd7da1dd6a7143b661e8107d255ce7f4a9997c7093b6c",
"index": 13,
"amount": 1,
"name": "Toro",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3250614d0b9cace98a5b9aad197a31262878ac6a70ae85b05c93622110873d08",
"index": 14,
"amount": 1,
"name": "2022 Ergo NFT Awards: NFT Project of the Year",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3699b932b8d2c40923a93c721d667fd64cd3e7918f4902e361d13dedfebde11d",
"index": 15,
"amount": 1,
"name": "Pynthe",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "cbd75cfe1a4f37f9a22eaee516300e36ea82017073036f07a09c1d2e10277cda",
"index": 16,
"amount": 199999002787,
"name": "hodlERG3",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "61d606459943c521061f63110496f9b9486e48518f845c74d24541f87d391f58",
"index": 17,
"amount": 1,
"name": "2022 Ergo NFT Awards: Favorite New NFT Project",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "96052f626de2203f8f9864fa183c5916af70cc6562a29d85a6531b3b4e947699",
"index": 18,
"amount": 1,
"name": "Mage Champions #706",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "38d841b370e21dfdafea7e9e8e2565636b12ec5024dfa6bee3c33057bca0295b",
"index": 19,
"amount": 1,
"name": "Icarnane",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "c0f0f79e9e69be8220d696eaef7205cac542aaf575c0ab760db7684c6ab54fc3",
"transactionId": "2356b8255effdd0e442ffce98cad285deb4d0a9ee281a5140d596ffe71a4c8e5",
"blockId": "a640d2eaa26b0433a92cd071a8c816b2b2d0bcec837fb4fc92dae58d31de40fc",
"value": 800000000000,
"index": 0,
"globalIndex": 46288558,
"creationHeight": 1462434,
"settlementHeight": 1462436,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(-105,-14,98,-87,-35,-29,-69,-127,-90,-128,-23,113,110,121,-64,-76,-26,-28,-24,-117,19,-9,-123,-84,-55,23,96,79,-64,36,37,-72,-89,-10,-44,-52,-15,40,-118,43,121,-29,-40,116,30,30,32,56,40,19,90,18,-71,47,-115,-60,-14,-46,30,64,115,-114,14,1)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val coll3 = Coll[Byte]()\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n val coll6 = placeholder[Coll[Byte]](3)\n val coll7 = coll6.slice(32, 64)\n val coll8 = placeholder[Coll[Byte]](0)\n val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n val coll10 = placeholder[Coll[Byte]](2)\n val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n val tuple15 = tuple13._2\n tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n }) }\n val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n val coll13 = Coll[Byte](\n 91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n )\n val b14 = getVar[Byte](0.toByte).get\n val func15 = {(box15: Box) => box15.tokens(1) }\n val i16 = INPUTS.indexOf(SELF, 0)\n val func17 = {(l17: Long) =>\n if (l17 < 128L) { 1 } else {\n if (l17 < 16384L) { 2 } else {\n if (l17 < 2097152L) { 3 } else {\n if (l17 < 268435456L) { 4 } else {\n if (l17 < 34359738368L) { 5 } else {\n if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val box21 = func1((OUTPUTS, coll20))(0)\n val coll22 = CONTEXT.dataInputs\n val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n val coll24 = opt4.getOrElse(coll3)\n val coll25 = func1((INPUTS, coll20))\n val l26 = func5(coll25)\n val box27 = func2((OUTPUTS, coll7))(0)\n val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte), Coll[Byte](79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n val l31 = func11((coll25, coll10))\n val coll32 = Coll[Box](box21)\n val l33 = func11((coll32, coll10))\n val l34 = func11((coll25, coll29))\n val l35 = func11((coll32, coll29))\n val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n val coll38 = tuple36._1\n (coll38 != coll10) && (coll38 != coll29)\n }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n val coll39 = tuple37._1\n (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n })\n anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte), coll13), coll24)\n val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n val bool42 = coll10 == coll29\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n )} else { false } }(b14)))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val coll21 = func1((INPUTS, coll20))\n val coll22 = func1((OUTPUTS, coll20))\n val l23 = func5(coll21)\n allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n val box22 = OUTPUTS(i16)\n val l23 = box22.value\n val l24 = SELF.value\n val coll25 = box22.propositionBytes\n val coll26 = SELF.bytesWithoutRef\n val coll27 = SELF.propositionBytes\n val i28 = SELF.creationInfo._1\n val coll29 = box22.bytesWithoutRef\n val i30 = box22.creationInfo._1\n allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n )} }((Coll[Byte](-57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "fc9b45c872ba69158c75b6e64efea34c476b15e0e3c27c070c30bc6c8d08f395",
"mainChain": true
},
{
"boxId": "a1bdb48e46365601423fee092159c874d40fda5758662317de2c60c9e5602ebf",
"transactionId": "2356b8255effdd0e442ffce98cad285deb4d0a9ee281a5140d596ffe71a4c8e5",
"blockId": "a640d2eaa26b0433a92cd071a8c816b2b2d0bcec837fb4fc92dae58d31de40fc",
"value": 1100000,
"index": 1,
"globalIndex": 46288559,
"creationHeight": 1462434,
"settlementHeight": 1462436,
"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": "bb4706b215671a3b11b4ffb48b3e67887f130cf55a571f625d4efb8f2342148b",
"mainChain": true
},
{
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"transactionId": "2356b8255effdd0e442ffce98cad285deb4d0a9ee281a5140d596ffe71a4c8e5",
"blockId": "a640d2eaa26b0433a92cd071a8c816b2b2d0bcec837fb4fc92dae58d31de40fc",
"value": 201047318342,
"index": 2,
"globalIndex": 46288560,
"creationHeight": 1462434,
"settlementHeight": 1462436,
"ergoTree": "0008cd036a496ea24cd4ad8465166161832ff49a98a9033956f0ccee63aade73b53c97d9",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6a496e,ce0996,...)))}",
"address": "9hGceS9rTZDDmsnioJGWykfUAzk8ZbCuuadNLvoeG7hN9bM3kNP",
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{
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"decimals": 0,
"type": "EIP-004"
},
{
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{
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{
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{
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},
{
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