Pith Number
pith:XETJF43J
pith:2024:XETJF43JZYA4XB5DG5RIBOQ6NW
not attested
not anchored
not stored
refs pending
A Scientific Machine Learning Approach for Predicting and Forecasting Battery Degradation in Electric Vehicles
arxiv:2410.14347 v1 · 2024-10-18 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{XETJF43JZYA4XB5DG5RIBOQ6NW}
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 | 2026-07-05T09:22:31.278771Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b92692f369ce01cb87a3376280ba1e6da39ec963a8b3913ce85c91fbeb45745e
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/XETJF43JZYA4XB5DG5RIBOQ6NW \
| 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: b92692f369ce01cb87a3376280ba1e6da39ec963a8b3913ce85c91fbeb45745e
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "2bbdd62a72668d36bee21a6e440d026bd2cb9bb633df053fce740f0f6dd50614",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-10-18T09:57:59Z",
"title_canon_sha256": "fc88cc1c5a88a602fc692554a1b773a102ac03c7b72765d5650d6e4a88945e73"
},
"schema_version": "1.0",
"source": {
"id": "2410.14347",
"kind": "arxiv",
"version": 1
}
}