Pith Number
pith:3AYM66ZY
pith:2022:3AYM66ZYDD367VCNB2JVSOEDQA
not attested
not anchored
not stored
refs pending
Deep Learning for Multiscale Damage Analysis via Physics-Informed Recurrent Neural Network
arxiv:2212.01880 v2 · 2022-12-04 · cs.CE
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{3AYM66ZYDD367VCNB2JVSOEDQA}
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
· sign in to
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 | 2026-07-05T05:28:48.657219Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d830cf7b3818f7efd44d0e9359388380355910d64cae0ba75af753a0be687dd3
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3AYM66ZYDD367VCNB2JVSOEDQA \
| 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: d830cf7b3818f7efd44d0e9359388380355910d64cae0ba75af753a0be687dd3
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "7643b7ccbda17f98372e895690bf9363fcbf4b4f38ce9629bcfc6117b31ed887",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CE",
"submitted_at": "2022-12-04T17:31:57Z",
"title_canon_sha256": "34ce751b88592aa8087333c67342fe4ceb97bfb43ffb3bfa277105d81a96deef"
},
"schema_version": "1.0",
"source": {
"id": "2212.01880",
"kind": "arxiv",
"version": 2
}
}