Pith Number
pith:MP63QWHI
pith:2025:MP63QWHICSUCJBDH6Y4A4K43J7
not attested
not anchored
not stored
refs pending
Generative AI as a Pillar for Predicting 2D and 3D Wildfire Spread: Beyond Physics-Based Models and Traditional Deep Learning
arxiv:2506.02485 v2 · 2025-06-03 · cs.AI · cs.CE
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{MP63QWHICSUCJBDH6Y4A4K43J7}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
Author claim
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claim
4
Citations
5
Replications
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Portable graph bundle live · download bundle · merged
state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same
current state with the deterministic merge algorithm.
Receipt and verification
| First computed | 2026-07-05T11:47:24.077175Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
63fdb858e814a8248467f6380e2b9b4fd227340dc53d69521226ffa18b2da8f5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MP63QWHICSUCJBDH6Y4A4K43J7 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 63fdb858e814a8248467f6380e2b9b4fd227340dc53d69521226ffa18b2da8f5
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "e7ae96af992b5bb8ae9df2b1175e745377d44fd9df9e656950d3630bfa45bdeb",
"cross_cats_sorted": [
"cs.CE"
],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "cs.AI",
"submitted_at": "2025-06-03T05:54:40Z",
"title_canon_sha256": "5a359a707564ae6fd038ae6295069b6568a94240636045e9f552a9b8dec710fc"
},
"schema_version": "1.0",
"source": {
"id": "2506.02485",
"kind": "arxiv",
"version": 2
}
}