Pith Number
pith:JJSLZSGE
pith:2025:JJSLZSGEBQJI2NM2EMLXIVDMWH
not attested
not anchored
not stored
refs pending
Bi-Residual Neural Network based Synchronous Motor Electrical Faults Diagnosis: Intra-link Layer Design for High-frequency Features
arxiv:2505.23097 v1 · 2025-05-29 · eess.SP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JJSLZSGEBQJI2NM2EMLXIVDMWH}
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 | 2026-07-05T11:11:55.438925Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4a64bcc8c40c128d359a231774546cb1c0ace0acb4444d017df59df9875def62
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JJSLZSGEBQJI2NM2EMLXIVDMWH \
| 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: 4a64bcc8c40c128d359a231774546cb1c0ace0acb4444d017df59df9875def62
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "6cf828622f46aac79348cc4a0092948f87a1a7092349fbc1bbe85e2c87f1ec35",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "eess.SP",
"submitted_at": "2025-05-29T05:01:40Z",
"title_canon_sha256": "3fb150079ac8587bd8c8166bef057f3b2abc029888283f34505620a2ab8a44f8"
},
"schema_version": "1.0",
"source": {
"id": "2505.23097",
"kind": "arxiv",
"version": 1
}
}