Pith Number
pith:RUJ4TXNB
pith:2026:RUJ4TXNBDBOAKWILS7H23BH7HQ
not attested
not anchored
not stored
refs pending
Agentic Anomaly Detection with ORCA-Style Dynamic Inductive Bias Adaptation in Multimodal Wearable Time Series Data
arxiv:2608.08859 v1 · 2026-08-09 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{RUJ4TXNBDBOAKWILS7H23BH7HQ}
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 | 2026-08-11T01:25:33.249630Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
8d13c9dda1185c05590b97cfad84ff3c0062a663173b2f13c3dbfd72bcf40c3e
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/RUJ4TXNBDBOAKWILS7H23BH7HQ \
| 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: 8d13c9dda1185c05590b97cfad84ff3c0062a663173b2f13c3dbfd72bcf40c3e
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "16efd15aeb0e6d6ce0e1656679c70eb62b638c8d49486b1717d8902035b396f2",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2026-08-09T18:49:13Z",
"title_canon_sha256": "13bef90b85f9f11d8b17ac14e6b691eb4189435c72cf4042436e1bc4d2d636b4"
},
"schema_version": "1.0",
"source": {
"id": "2608.08859",
"kind": "arxiv",
"version": 1
}
}