Pith Number
pith:WBJFIIUS
pith:2025:WBJFIIUSJWWMVXXZR2Q5CR5Y7V
not attested
not anchored
not stored
refs pending
A scalable Bayesian double machine learning framework, with application to racial disproportionality assessment
arxiv:2502.07695 v3 · 2025-02-11 · stat.AP · stat.ME
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{WBJFIIUSJWWMVXXZR2Q5CR5Y7V}
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 | 2026-06-12T01:09:07.260457Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b0525422924daccadef98ea1d147b8fd5cb74168352533eaa1ceecfe9a5d23ae
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WBJFIIUSJWWMVXXZR2Q5CR5Y7V \
| 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: b0525422924daccadef98ea1d147b8fd5cb74168352533eaa1ceecfe9a5d23ae
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "fd96469f509cca0762ed3fc0c907be4c0649026a06cc6ecd3c0561c5ffeabb99",
"cross_cats_sorted": [
"stat.ME"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.AP",
"submitted_at": "2025-02-11T16:48:55Z",
"title_canon_sha256": "12c5412a5d945de05ffd027855d638cf3042c4615118c8f294f242be0d4631dc"
},
"schema_version": "1.0",
"source": {
"id": "2502.07695",
"kind": "arxiv",
"version": 3
}
}