Pith Number
pith:55COL3QN
pith:2025:55COL3QN7U6JYER4DZ3DFHP7ZS
not attested
not anchored
not stored
refs pending
Using Large Language Models to Suggest Informative Prior Distributions in Bayesian Statistics
arxiv:2506.21964 v1 · 2025-06-27 · stat.ME · cs.AI · cs.CL
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{55COL3QN7U6JYER4DZ3DFHP7ZS}
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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.
Cited by
Receipt and verification
| First computed | 2026-07-05T11:28:19.309887Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
ef44e5ee0dfd3c9c123c1e76329dffcc8225676f5f7a596b62bcbd17cd22bf3e
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/55COL3QN7U6JYER4DZ3DFHP7ZS \
| 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: ef44e5ee0dfd3c9c123c1e76329dffcc8225676f5f7a596b62bcbd17cd22bf3e
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "54cf20050463da43ca381ed8c5c144d70cc8f62dc1304f3ab505e7af42949d82",
"cross_cats_sorted": [
"cs.AI",
"cs.CL"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "stat.ME",
"submitted_at": "2025-06-27T07:11:55Z",
"title_canon_sha256": "69c4530dff8bfb82662b1c04151937d270e21cdd13698add7d5dabf56093fcf5"
},
"schema_version": "1.0",
"source": {
"id": "2506.21964",
"kind": "arxiv",
"version": 1
}
}