Pith Number
pith:DDFXJ4ZH
pith:2019:DDFXJ4ZH3M4IYN6RMT3JUFOJHX
not attested
not anchored
not stored
refs pending
Learning Multimorbidity Patterns from Electronic Health Records Using Non-negative Matrix Factorisation
arxiv:1907.08577 v2 · 2019-07-19 · stat.ML · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{DDFXJ4ZH3M4IYN6RMT3JUFOJHX}
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 | 2026-07-05T00:20:01.245629Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
18cb74f327db388c37d164f69a15c93dc64870b881e55b4f1b5192bec2ac682b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/DDFXJ4ZH3M4IYN6RMT3JUFOJHX \
| 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: 18cb74f327db388c37d164f69a15c93dc64870b881e55b4f1b5192bec2ac682b
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "1260b90c9c5ec93adf6de3051df9eae5d42559876e0b294019fc36234396f9e0",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.ML",
"submitted_at": "2019-07-19T17:03:44Z",
"title_canon_sha256": "ef0363363fe51506e5c8e7f9927a1727340a388cf6e5903ec711bd5ed561d516"
},
"schema_version": "1.0",
"source": {
"id": "1907.08577",
"kind": "arxiv",
"version": 2
}
}