Pith Number
pith:KDUMNGXV
pith:2026:KDUMNGXVSHMM5TAXF7B7QJRD66
not attested
not anchored
not stored
refs pending
Trajectory-Aware Clinical Risk Prediction via Severity-Grounded Knowledge Graphs and Retrieval-Augmented Generation
arxiv:2607.18270 v1 · 2026-06-02 · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{KDUMNGXVSHMM5TAXF7B7QJRD66}
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 | 2026-07-22T00:22:39.493893Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
50e8c69af591d8cecc172fc3f82623f79ad9ed8437b2a7561b3175f04e583c0b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/KDUMNGXVSHMM5TAXF7B7QJRD66 \
| 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: 50e8c69af591d8cecc172fc3f82623f79ad9ed8437b2a7561b3175f04e583c0b
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "3be39c8c0c5c01051296be0e596a69c3bec63c1e3ef1b1098e845daea729335c",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.AI",
"submitted_at": "2026-06-02T04:32:32Z",
"title_canon_sha256": "846099fd702f7e902a8ad718524e81b713f1695c9e526e20c11faf391332c2d7"
},
"schema_version": "1.0",
"source": {
"id": "2607.18270",
"kind": "arxiv",
"version": 1
}
}