Pith Number
pith:GPN3QXQT
pith:2025:GPN3QXQTHVSOV7RYI5HTDM6CKZ
not attested
not anchored
not stored
refs pending
Deep learning approaches for nuclear binding energy prediction: a comparative study of RNN, GRU and LSTM Models
arxiv:2503.19348 v1 · 2025-03-25 · nucl-th
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{GPN3QXQTHVSOV7RYI5HTDM6CKZ}
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
✓
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 | 2026-07-05T10:38:53.520395Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
33dbb85e133d64eafe38474f31b3c2567185827f33461a0a62e5bbb625596204
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GPN3QXQTHVSOV7RYI5HTDM6CKZ \
| 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: 33dbb85e133d64eafe38474f31b3c2567185827f33461a0a62e5bbb625596204
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "7a32821668a0690175c042b77a666ab3ceeddf01f259e9242898b6267a302fd4",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "nucl-th",
"submitted_at": "2025-03-25T04:55:27Z",
"title_canon_sha256": "6de6e0c13877510c815dfe126eb02115012a4c62e0b85516b64c6b394e9b1407"
},
"schema_version": "1.0",
"source": {
"id": "2503.19348",
"kind": "arxiv",
"version": 1
}
}