Pith Number
pith:2AA22LJP
pith:2017:2AA22LJPRD7B6DQIO7ED5HU7BN
not attested
not anchored
not stored
refs pending
Using Bayesian latent Gaussian graphical models to infer symptom associations in verbal autopsies
arxiv:1711.00877 v4 · 2017-11-02 · stat.AP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{2AA22LJPRD7B6DQIO7ED5HU7BN}
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 | 2026-05-17T23:39:42.061557Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d001ad2d2f88fe1f0e0877c83e9e9f0b5c7214340148e29eb98e762aba03b900
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/2AA22LJPRD7B6DQIO7ED5HU7BN \
| 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: d001ad2d2f88fe1f0e0877c83e9e9f0b5c7214340148e29eb98e762aba03b900
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "e73abf423049d6091f885b897178e91f242328953740f05660cd03b9d3371570",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.AP",
"submitted_at": "2017-11-02T18:29:13Z",
"title_canon_sha256": "728f2c937e38f39b9b66fa35de528e63575fb310a3a069720912aefcd041a37e"
},
"schema_version": "1.0",
"source": {
"id": "1711.00877",
"kind": "arxiv",
"version": 4
}
}