Pith Number
pith:56RNEJZK
pith:2025:56RNEJZK6PMHAHNNCHL5274NWY
not attested
not anchored
not stored
refs pending
PINT: Physics-Informed Neural Time Series Models with Applications to Long-term Inference on WeatherBench 2m-Temperature Data
arxiv:2502.04018 v2 · 2025-02-06 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{56RNEJZK6PMHAHNNCHL5274NWY}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T11:38:50.126141Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
efa2d2272af3d8701dad11d7dd7f8db620540a972cd628fedafe5c3252ab35a8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/56RNEJZK6PMHAHNNCHL5274NWY \
| 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: efa2d2272af3d8701dad11d7dd7f8db620540a972cd628fedafe5c3252ab35a8
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "552deaa6eedaaae0eca2d418b02beed873aa5caf6a2a36b8c13f50052f323b6e",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-02-06T12:19:34Z",
"title_canon_sha256": "2acb2223aa579d4037e5c362f2c87c7b19207ad2dc4ccd5b390120c0c7c3a570"
},
"schema_version": "1.0",
"source": {
"id": "2502.04018",
"kind": "arxiv",
"version": 2
}
}