Pith Number
pith:JYVHZKHB
pith:2026:JYVHZKHBQ2V27HRFAKTNCXQXOT
not attested
not anchored
not stored
refs pending
LLM Doesn't Know What It Doesn't Know: Detecting Epistemic Blind Spots via Cross-Model Attribution Divergence on Clinical Tabular Data
arxiv:2606.19509 v1 · 2026-06-17 · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JYVHZKHBQ2V27HRFAKTNCXQXOT}
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
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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 | 2026-06-19T16:12:27.491871Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4e2a7ca8e186abaf9e2502a6d15e1774da1e47c99e0f5da6d8981bcbd452832e
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JYVHZKHBQ2V27HRFAKTNCXQXOT \
| 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: 4e2a7ca8e186abaf9e2502a6d15e1774da1e47c99e0f5da6d8981bcbd452832e
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "23705e60a534e3c0ebff2389dcc9c3ed2c2c30e5035db981a04a7bfdd867de68",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.AI",
"submitted_at": "2026-06-17T18:49:44Z",
"title_canon_sha256": "c5f64176a4dd739d08aad79e641d15a4e9dc6820bf15b56e4683d81889fbe814"
},
"schema_version": "1.0",
"source": {
"id": "2606.19509",
"kind": "arxiv",
"version": 1
}
}