Pith Number
pith:Q5KQLFVP
pith:2025:Q5KQLFVPPDIM4VVTPSANF6CJ77
not attested
not anchored
not stored
refs pending
Two-stage MCMC for Fast Bayesian Inference of Large Spatio-temporal Ordinal Data, with Application to US Drought
arxiv:2505.24594 v1 · 2025-05-30 · stat.ME · stat.AP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{Q5KQLFVPPDIM4VVTPSANF6CJ77}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T11:12:52.896496Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
87550596af78d0ce56b37c80d2f849ffde8cca96cdb5fc1564146dfd3ee3ec2d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/Q5KQLFVPPDIM4VVTPSANF6CJ77 \
| 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: 87550596af78d0ce56b37c80d2f849ffde8cca96cdb5fc1564146dfd3ee3ec2d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "db73aced684f2438f516c7ad83e16fe0f22464e43d74f2f190152c28a2692dfd",
"cross_cats_sorted": [
"stat.AP"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "stat.ME",
"submitted_at": "2025-05-30T13:41:34Z",
"title_canon_sha256": "05f66509945df43d09582fe91b485fa3033221ae0cbdbc2c62110d7cdf182bea"
},
"schema_version": "1.0",
"source": {
"id": "2505.24594",
"kind": "arxiv",
"version": 1
}
}