Pith Number
pith:SNFVY4GG
pith:2019:SNFVY4GGFFM5YVPNHCLUEIHNQR
not attested
not anchored
not stored
refs pending
Recurrent Neural Networks with Long Term Temporal Dependencies in Machine Tool Wear Diagnosis and Prognosis
arxiv:1907.11848 v1 · 2019-07-27 · eess.SP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{SNFVY4GGFFM5YVPNHCLUEIHNQR}
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.
Receipt and verification
| First computed | 2026-05-17T23:39:22.848354Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
934b5c70c62959dc55ed38974220ed844d0b95e010c331c2ef58751610837c88
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/SNFVY4GGFFM5YVPNHCLUEIHNQR \
| 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: 934b5c70c62959dc55ed38974220ed844d0b95e010c331c2ef58751610837c88
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "e2c3f7f822e44d6ca6d092edf1cb7d852b6464ebfe1a06fd7f44ca49fd9c2ebf",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "eess.SP",
"submitted_at": "2019-07-27T04:42:29Z",
"title_canon_sha256": "0ef4397bce886772c6f743cb95cab74c6eb4dd68697a8607c178f6b99fb3cf3c"
},
"schema_version": "1.0",
"source": {
"id": "1907.11848",
"kind": "arxiv",
"version": 1
}
}