Token
67a38375c946e0265aea73429f796f7d94f0bee1b9ed18ab42466fadd2985945
ID
67a38375c946e0265aea73429f796f7d94f0bee1b9ed18ab42466fadd2985945
Name
ERGO | CREATION | 04
Emission amount
1
Decimals
0
Description
Linked to the ERGO FILM SERIES is our exclusive NFT range. With each film there will be SIX NFT's released, five up for auction and the other donated to a core member of the Ergo Team each time.
There are FOUR artworks each featuring one of the main "Therefore / Ergo" script tag-lines making up the narrative of the film.
Then there is TWO artworks forming the MASTER which consists of all four of the above portraits combined. Only one of these master NFT's are up for grabs and the other is the donation piece.
PART 01 of the NFT range is titled CREATION and is linked to the film: https://youtu.be/mwIWm-1B2eM
It's only fit that the CREATION NFT MASTER is donated to the CREATOR of Ergo so if you want to own a similar master or linked piece of the same goodness as Kushti make sure you get your bids going.
Big and beautiful these NFT artworks are all 7015 px × 9614px (A1) hi-res .png files and not to be missed, but exclusivity and creations like these do come at a price and sets the foundation for future worth.
If you're serious about art, Ergo and believe in NFT's as an investment, these are for you.
Type
EIP-004
Issuer Box
{
"boxId": "67a38375c946e0265aea73429f796f7d94f0bee1b9ed18ab42466fadd2985945",
"transactionId": "2da213d8286ccdb0d2f945e0d124876caa12240d07652b988f3c9884bf693f9c",
"blockId": "454bb525ff9852ff79b51e911bf2132c5096f38f15a10948d76fb2cbd016d205",
"value": 2000000,
"index": 0,
"globalIndex": 13884172,
"creationHeight": 698680,
"settlementHeight": 698682,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 2\n5: 1\n6: 1000000\n7: Coll(0,8,-51,2,91,21,116,7,87,111,-116,117,-83,95,19,-20,-58,44,-31,90,112,-60,3,-9,94,-13,19,23,77,123,104,86,-105,105,82,-113)\n8: Coll(1,1)\n9: Coll(-121,63,127,-20,12,-11,124,-54,126,79,-34,33,0,14,-35,-103,-61,23,37,1,110,93,-92,95,-69,-94,13,41,-101,-23,-48,91)\n10: 0\n11: 4000000\n12: Coll(0,8,-51,2,91,21,116,7,87,111,-116,117,-83,95,19,-20,-58,44,-31,90,112,-60,3,-9,94,-13,19,23,77,123,104,86,-105,105,82,-113)\n13: 1646376720553",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val l2 = box1.value\n val coll3 = INPUTS(placeholder[Int](1)).id\n val tuple4 = box1.tokens.getOrElse(placeholder[Int](2), (coll3, placeholder[Long](3)))\n sigmaProp(\n (\n (OUTPUTS.size == placeholder[Int](4)) && (\n (\n (\n (\n (((coll3 == tuple4._1) && (tuple4._2 == placeholder[Long](5))) && (l2 == placeholder[Long](6))) && (\n box1.propositionBytes == placeholder[Coll[Byte]](7)\n )\n ) && (box1.R7[Coll[Byte]].get == placeholder[Coll[Byte]](8))\n ) && (box1.R8[Coll[Byte]].get == placeholder[Coll[Byte]](9))\n ) || (\n (l2 >= INPUTS.fold(placeholder[Long](10), {(tuple5: (Long, Box)) => tuple5._1 + tuple5._2.value }) - placeholder[Long](11)) && (\n box1.propositionBytes == placeholder[Coll[Byte]](12)\n )\n )\n )\n ) && (HEIGHT.toLong < placeholder[Long](13))\n )\n}",
"address": "2eR9oDmG9onJa8DfTAoSMZUXWQFD3iMhsWENUfTBPBR98rTkgGMpSRbuLdoyDFrM7FHWvJArkkxG8KAMrLyXco4gsT542QZDFKyoVaCE147FjRx5bzuxQk4PED78PaRKtejMiNd7TNFtvztfMqxpH93ZVhqMoWrFXzav1i8aUka1dm8j2556p46Qocc4vcKDio5x4yyFaZT1T5eRQ4AndYzWb6ED9oojXkZHiPyingDMC1QRAT6NbyT8TjcG2Dob8fRYWqioUe1zLyr4GwjRZbiBHU1dVsdKucZeZhWCgTY6qk4WvKJvaW4Qv8bLKcxcwdmNwnBinGMHhEPANcbDfB7LUmz3optfyyWBYnRezCz67pJsF7seekqzmVDy6Td8CZmQW",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0464",
"sigmaType": "SInt",
"renderedValue": "50"
},
"R5": {
"serializedValue": "0e240008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd025b157407576f8c75ad5f13ecc62ce15a70c403f75ef313174d7b68569769528f"
}
},
"spentTransactionId": "2450f2464bddbb73414402c49ec4e1b4a07629f365c89c2e7ef357052c1bfb05",
"mainChain": true
}