Transaction
ID: 74e7b9efdd...c6da
Inputs (3)
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:
136.25 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
0
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
0
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
136.25 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 207,112
Total coins transferred: 136.26 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000001002 ERG
Raw Transaction Data
{
"id": "74e7b9efdd2de07fa477093ea2a2164fea202b1445c284b04fe4d6639686c6da",
"blockId": "65f4f26f8a83d2897e750a57e1a2814b4edc1959b10f9cba02b17054405db9e6",
"inclusionHeight": 1554109,
"timestamp": 1750776517398,
"index": 1,
"globalIndex": 9122738,
"numConfirmations": 207112,
"inputs": [
{
"boxId": "70a1becd25edf31802019811b658e72db065f90134556468d419f49b40738e89",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "cbddf54961c852e07c1dabc45b0c852b78d0fa004ea415eaf720a0b7b12b4598",
"outputTransactionId": "d33f40bacbc78f94a19bbf81a0bb41235bd60b3d83f2bac6d2d5209b5f00f0ec",
"outputIndex": 0,
"outputGlobalIndex": 48527195,
"outputCreatedAt": 1554100,
"outputSettledAt": 1554104,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-21,14,81,-108,2,-33,-44,121,81,-71,-58,-66,-73,-35,-56,-55,-23,112,-128,47,70,-16,-24,-78,-96,41,-116,8,-41,-63,46,49)\n1: SigmaProp(ProveDlog(ECPoint(75acc4,25ee17,...)))\n2: 0\n3: 0\n4: 1\n5: 127\n6: 3\n7: 2\n8: 0\n9: 1\n10: Coll(0,8,-51,2,18,-119,25,-122,77,69,118,50,84,63,54,-89,67,122,-126,85,-111,83,86,57,-80,19,-28,1,-39,4,63,83,-32,-125,-69,-113)\n11: 720\n12: 0\n13: 720\n14: 0\n15: 0\n16: 30\n17: 8\n18: 1\n19: 1\n20: 0\n21: 1\n22: 1\n23: true\n24: false\n25: 0\n26: 10\n27: 100\n28: 0\n29: 1\n30: 2\n31: 1\n32: 0\n33: 1\n34: 0\n35: 2\n36: 2\n37: 0\n38: 60\n39: 0\n40: 3\n41: 1\n42: 0\n43: 2\n44: 1\n45: 2\n46: 2\n47: 0\n48: 0\n49: false\n50: 0\n51: 0\n52: false\n53: 0\n54: true\n55: 4\n56: 1\n57: 0\n58: 0\n59: 5\n60: 1\n61: 0\n62: 0\n63: 800\n64: 1000\n65: 1\n66: 120\n67: 1000\n68: 0\n69: 2\n70: 30\n71: 1000\n72: 0\n73: 3\n74: 2\n75: 1\n76: 0\n77: 0\n78: true\n79: 0\n80: true\n81: 6\n82: 0\n83: 1\n84: 0\n85: 1\n86: 7\n87: 0\n88: 0\n89: 2\n90: 1\n91: 0\n92: 1\n93: 8\n94: 1\n95: 120\n96: 1000\n97: 0\n98: 2\n99: 30\n100: 1000\n101: 0\n102: 3\n103: 2\n104: 1\n105: 0\n106: 1\n107: 0\n108: true\n109: 0\n110: true\n111: 800\n112: 1000\n113: 9\n114: 0\n115: 0\n116: 1\n117: 0\n118: 1\n119: false",
"ergoTreeScript": "{\n val i1 = getVar[Int](0.toByte).get\n val func2 = {(box2: Box) => box2.tokens.exists({(tuple4: (Coll[Byte], Long)) => tuple4._1 == placeholder[Coll[Byte]](0) }) }\n val prop3 = placeholder[SigmaProp](1)\n val func4 = {(tuple4: (SigmaProp, Box)) =>\n val coll6 = tuple4._2.propositionBytes\n val coll7 = tuple4._1.propBytes\n if (coll6(placeholder[Int](2)).toInt == placeholder[Int](3)) { coll6 == coll7 } else {(\n val i8 = coll6.size\n coll7.slice(placeholder[Int](4), coll7.size) == coll6.slice(if (i8 > placeholder[Int](5)) { placeholder[Int](6) } else { placeholder[Int](7) }, i8)\n )}\n }\n val l5 = SELF.R8[Long].get\n val coll6 = SELF.propositionBytes\n val coll7 = SELF.tokens\n val tuple8 = coll7(placeholder[Int](8))\n val coll9 = tuple8._1\n val tuple10 = coll7(placeholder[Int](9))\n val coll11 = tuple10._1\n val i12 = SELF.R4[Int].get\n val tuple13 = SELF.R5[(SigmaProp, SigmaProp)].get\n val prop14 = tuple13._1\n val tuple15 = SELF.R6[(Coll[Byte], Coll[Byte])].get\n val prop16 = tuple13._2\n val l17 = SELF.R9[Long].get\n val coll18 = placeholder[Coll[Byte]](10)\n val func19 = {(coll19: Coll[Byte]) =>\n OUTPUTS.forall(\n {(box21: Box) => allOf(Coll[Boolean](box21.tokens.forall({(tuple23: (Coll[Byte], Long)) => tuple23._1 != coll19 }), box21.propositionBytes != coll6)) }\n )\n }\n val tuple20 = SELF.R7[(Boolean, Boolean)].get\n val bool21 = tuple20._1\n val i22 = i12 - HEIGHT\n val bool23 = (i22 < placeholder[Int](11)) && (i22 > placeholder[Int](12))\n val bool24 = i22 >= placeholder[Int](13)\n val bool25 = tuple20._2\n val coll26 = tuple15._1\n val bool27 = coll26.size > placeholder[Int](14)\n val coll28 = tuple15._2\n val bool29 = coll28.size > placeholder[Int](15)\n val i30 = i12 + placeholder[Int](16)\n val i31 = i30 + placeholder[Int](17)\n if (i1 == placeholder[Int](18)) {(\n val box32 = INPUTS(placeholder[Int](19))\n val box33 = OUTPUTS(placeholder[Int](20))\n val tuple34 = box33.R5[(SigmaProp, SigmaProp)].get\n val prop35 = tuple34._2\n val l36 = box33.R9[Long].get\n val coll37 = box33.tokens\n val tuple38 = coll37(placeholder[Int](21))\n val box39 = OUTPUTS(placeholder[Int](22))\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n func2(box32), allOf(\n Coll[Boolean](prop35 != prop3, func4((prop35, box32)), box33.R7[(Boolean, Boolean)].get == (placeholder[Boolean](23), placeholder[Boolean](24)))\n )\n )\n ), allOf(Coll[Boolean](l36 > placeholder[Long](25), l36 == placeholder[Long](26) * l5 / placeholder[Long](27), tuple38._2 == l5 + l36)), allOf(\n Coll[Boolean](\n box33.value == SELF.value, box33.propositionBytes == coll6, coll37(placeholder[Int](28)) == (\n coll9, placeholder[Long](29)\n ), tuple38._1 == coll11, box33.R4[Int].get == i12, tuple34._1 == prop14, box33.R6[(Coll[Byte], Coll[Byte])].get == tuple15, box33.R8[\n Long\n ].get == l5\n )\n ), allOf(Coll[Boolean](box39.propositionBytes == box32.propositionBytes, func2(box39)))\n )\n )\n )\n )} else { if (i1 == placeholder[Int](30)) {(\n val box32 = INPUTS(placeholder[Int](31))\n val box33 = OUTPUTS(placeholder[Int](32))\n val box34 = OUTPUTS(placeholder[Int](33))\n val tuple35 = box34.tokens(placeholder[Int](34))\n val l36 = l17 / placeholder[Long](35)\n val box37 = OUTPUTS(placeholder[Int](36))\n val tuple38 = box37.tokens(placeholder[Int](37))\n sigmaProp(allOf(Coll[Boolean](bool21, i22 >= placeholder[Int](38), allOf(Coll[Boolean](func4((prop16, box32)), func2(box32))), allOf(Coll[Boolean](func4((prop14, box33)), box33.tokens(placeholder[Int](39)) == (coll11, l5))), allOf(Coll[Boolean](box34.propositionBytes == box32.propositionBytes, allOf(Coll[Boolean](tuple35._1 == coll11, tuple35._2 == l36)), func2(box34))), allOf(Coll[Boolean](box37.propositionBytes == coll18, allOf(Coll[Boolean](tuple38._1 == coll11, tuple38._2 == tuple10._2 - l5 - l36)))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](40)) {(\n val box32 = INPUTS(placeholder[Int](41))\n val box33 = OUTPUTS(placeholder[Int](42))\n val l34 = l5 / placeholder[Long](43)\n val box35 = OUTPUTS(placeholder[Int](44))\n val l36 = l5 - l34\n val l37 = l36 / placeholder[Long](45)\n val box38 = OUTPUTS.getOrElse(placeholder[Int](46), SELF)\n sigmaProp(allOf(Coll[Boolean](bool21, func4((prop14, box32)), allOf(Coll[Boolean](box33.propositionBytes == box32.propositionBytes, if (bool24) { box33.tokens(placeholder[Int](47)) == (coll11, l5) } else { if (bool23) { box33.tokens(placeholder[Int](48)) == (coll11, l34) } else { placeholder[Boolean](49) } })), allOf(Coll[Boolean](func4((prop16, box35)), if (bool24) {(\n val tuple39 = box35.tokens(placeholder[Int](50))\n allOf(Coll[Boolean](tuple39._1 == coll11, tuple39._2 == l17))\n )} else { if (bool23) {(\n val tuple39 = box35.tokens(placeholder[Int](51))\n allOf(Coll[Boolean](tuple39._1 == coll11, tuple39._2 == l17 + l36 - l37))\n )} else { placeholder[Boolean](52) } })), if (bool23) {(\n val tuple39 = box38.tokens(placeholder[Int](53))\n allOf(Coll[Boolean](box38.propositionBytes == coll18, allOf(Coll[Boolean](tuple39._1 == coll11, tuple39._2 == l37))))\n )} else { placeholder[Boolean](54) }, func19(coll9))))\n )} else { if (i1 == placeholder[Int](55)) {(\n val box32 = INPUTS(placeholder[Int](56))\n val box33 = OUTPUTS(placeholder[Int](57))\n sigmaProp(allOf(Coll[Boolean](!bool21, func4((prop14, box32)), allOf(Coll[Boolean](box33.propositionBytes == box32.propositionBytes, box33.tokens(placeholder[Int](58)) == (coll11, l5))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](59)) {(\n val box32 = INPUTS(placeholder[Int](60))\n val box33 = OUTPUTS(placeholder[Int](61))\n val tuple34 = box33.tokens(placeholder[Int](62))\n val l35 = placeholder[Long](63) * l5 / placeholder[Long](64)\n val box36 = OUTPUTS.getOrElse(placeholder[Int](65), SELF)\n val l37 = if (bool27) { placeholder[Long](66) * l5 / placeholder[Long](67) } else { placeholder[Long](68) }\n val box38 = OUTPUTS.getOrElse(placeholder[Int](69), SELF)\n val l39 = if (bool29) { placeholder[Long](70) * l5 / placeholder[Long](71) } else { placeholder[Long](72) }\n val box40 = if (bool27 && bool29) { OUTPUTS(placeholder[Int](73)) } else { if (bool27) { OUTPUTS(placeholder[Int](74)) } else { OUTPUTS(placeholder[Int](75)) } }\n val tuple41 = box40.tokens(placeholder[Int](76))\n sigmaProp(allOf(Coll[Boolean](HEIGHT >= i30, HEIGHT >= i31, bool21, !bool25, allOf(Coll[Boolean](func4((prop16, box32)), func2(box32))), allOf(Coll[Boolean](box33.propositionBytes == box32.propositionBytes, allOf(Coll[Boolean](tuple34._1 == coll11, tuple34._2 == l17 + l35)), func2(box33))), if (bool27) {(\n val tuple42 = box36.tokens(placeholder[Int](77))\n allOf(Coll[Boolean](box36.propositionBytes == coll26, allOf(Coll[Boolean](tuple42._1 == coll11, tuple42._2 == l37))))\n )} else { placeholder[Boolean](78) }, if (bool29 && bool27) {(\n val tuple42 = box38.tokens(placeholder[Int](79))\n allOf(Coll[Boolean](box38.propositionBytes == coll28, allOf(Coll[Boolean](tuple42._1 == coll11, tuple42._2 == l39))))\n )} else { placeholder[Boolean](80) }, allOf(Coll[Boolean](box40.propositionBytes == coll18, allOf(Coll[Boolean](tuple41._1 == coll11, tuple41._2 == l5 - l35 + l37 + l39)))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](81)) {(\n val box32 = OUTPUTS(placeholder[Int](82))\n val tuple33 = box32.R7[(Boolean, Boolean)].get\n val coll34 = box32.tokens\n sigmaProp(allOf(Coll[Boolean]((HEIGHT >= i12) && bool21, HEIGHT < i31, func4((prop14, INPUTS(placeholder[Int](83)))), tuple33._2, allOf(Coll[Boolean](box32.value == SELF.value, box32.propositionBytes == coll6, coll34(placeholder[Int](84)) == tuple8, coll34(placeholder[Int](85)) == tuple10, box32.R4[Int].get == i12, box32.R5[(SigmaProp, SigmaProp)].get == tuple13, box32.R6[(Coll[Byte], Coll[Byte])].get == tuple15, tuple33._1 == bool21, box32.R8[Long].get == l5, box32.R9[Long].get == l17)))))\n )} else { if (i1 == placeholder[Int](86)) {(\n val box32 = OUTPUTS(placeholder[Int](87))\n val tuple33 = box32.tokens(placeholder[Int](88))\n val l34 = l17 / placeholder[Long](89)\n val box35 = OUTPUTS(placeholder[Int](90))\n val tuple36 = box35.tokens(placeholder[Int](91))\n sigmaProp(allOf(Coll[Boolean](bool25, func4((prop3, INPUTS(placeholder[Int](92)))), allOf(Coll[Boolean](func4((prop14, box32)), allOf(Coll[Boolean](tuple33._1 == coll11, tuple33._2 == l34 + l5)))), allOf(Coll[Boolean](box35.propositionBytes == coll18, allOf(Coll[Boolean](tuple36._1 == coll11, tuple36._2 == l17 - l34)))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](93)) {(\n val box32 = OUTPUTS.getOrElse(placeholder[Int](94), SELF)\n val l33 = if (bool27) { placeholder[Long](95) * l5 / placeholder[Long](96) } else { placeholder[Long](97) }\n val box34 = OUTPUTS.getOrElse(placeholder[Int](98), SELF)\n val l35 = if (bool29) { placeholder[Long](99) * l5 / placeholder[Long](100) } else { placeholder[Long](101) }\n val box36 = if (bool27 && bool29) { OUTPUTS(placeholder[Int](102)) } else { if (bool27) { OUTPUTS(placeholder[Int](103)) } else { OUTPUTS(placeholder[Int](104)) } }\n val tuple37 = box36.tokens(placeholder[Int](105))\n sigmaProp(allOf(Coll[Boolean](bool25, func4((prop3, INPUTS(placeholder[Int](106)))), if (bool27) {(\n val tuple38 = box32.tokens(placeholder[Int](107))\n allOf(Coll[Boolean](box32.propositionBytes == coll26, allOf(Coll[Boolean](tuple38._1 == coll11, tuple38._2 == l33))))\n )} else { placeholder[Boolean](108) }, if (bool29 && bool27) {(\n val tuple38 = box34.tokens(placeholder[Int](109))\n allOf(Coll[Boolean](box34.propositionBytes == coll28, allOf(Coll[Boolean](tuple38._1 == coll11, tuple38._2 == l35))))\n )} else { placeholder[Boolean](110) }, allOf(Coll[Boolean](box36.propositionBytes == coll18, allOf(Coll[Boolean](tuple37._1 == coll11, tuple37._2 == l5 - placeholder[Long](111) * l5 / placeholder[Long](112) + l33 + l35)))), func19(coll9))))\n )} else { if (i1 == placeholder[Int](113)) {(\n val box32 = OUTPUTS(placeholder[Int](114))\n val tuple33 = box32.tokens(placeholder[Int](115))\n val box34 = OUTPUTS(placeholder[Int](116))\n val tuple35 = box34.tokens(placeholder[Int](117))\n sigmaProp(allOf(Coll[Boolean](bool25, func4((prop3, INPUTS(placeholder[Int](118)))), allOf(Coll[Boolean](func4((prop14, box32)), allOf(Coll[Boolean](tuple33._1 == coll11, tuple33._2 == l5)))), allOf(Coll[Boolean](func4((prop16, box34)), allOf(Coll[Boolean](tuple35._1 == coll11, tuple35._2 == l17)))), func19(coll9))))\n )} else { sigmaProp(placeholder[Boolean](119)) } } } } } } } } }\n}",
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"assets": [
{
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},
{
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"index": 1,
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"name": "SigUSD",
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"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "(SSigmaProp, SSigmaProp)",
"renderedValue": "[02bd32719211271080424d666d895c89c7c23c43f12a86042639c7fe81fda90508,02627b2ae20e2f69ef4fc16569f8474ed850c7b87fc312aa21002e63f6dc0c43bc]"
},
"R6": {
"serializedValue": "3c0e0e0000",
"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[,]"
},
"R8": {
"serializedValue": "0528",
"sigmaType": "SLong",
"renderedValue": "20"
},
"R7": {
"serializedValue": "550100",
"sigmaType": "(SBoolean, SBoolean)",
"renderedValue": "[true,false]"
},
"R9": {
"serializedValue": "0504",
"sigmaType": "SLong",
"renderedValue": "2"
},
"R4": {
"serializedValue": "04889cbe01",
"sigmaType": "SInt",
"renderedValue": "1558276"
}
}
},
{
"boxId": "0c5c3da534def36937dbc71852ab110ac351ebbb8c576761296a62324bb8266a",
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"index": 1,
"spendingProof": "33e72a16368e5aa377cd8e324953d11bc3279e89e6c848cee67805249dc17c2589b24f94129d18ea8f5a9144af5624d2ffe28f4816a42436",
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"outputIndex": 1,
"outputGlobalIndex": 48527196,
"outputCreatedAt": 1554100,
"outputSettledAt": 1554104,
"ergoTree": "0008cd02627b2ae20e2f69ef4fc16569f8474ed850c7b87fc312aa21002e63f6dc0c43bc",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(627b2a,4dc0a9,...)))}",
"address": "9fGS5mw42MPszcjurgijPP3Abqc47Gm8rwUrqM7TQMBY3AFNRWB",
"assets": [
{
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"index": 0,
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"name": "PsychologistPass",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
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{
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{
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{
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{
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{
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{
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},
{
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{
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{
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{
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{
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{
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{
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},
{
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{
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],
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}
],
"dataInputs": [],
"outputs": [
{
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"transactionId": "74e7b9efdd2de07fa477093ea2a2164fea202b1445c284b04fe4d6639686c6da",
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"address": "9fxPJLBUSJ6s5BrStXDrH7coergyyrzdPjmDPDtf8X5inT8DQxs",
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],
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{
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{
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{
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