Pith Number
pith:VLMCN63Z
pith:2023:VLMCN63ZWNBDU5SLYPAOFZHNWK
not attested
not anchored
not stored
refs pending
Is control of type I error rate needed in Bayesian clinical trial designs?
arxiv:2312.15222 v6 · 2023-12-23 · stat.ME
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{VLMCN63ZWNBDU5SLYPAOFZHNWK}
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 | 2026-07-30T01:18:37.458558Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | unsigned_v0 |
| Schema | pith-number/v1.0 |
Canonical hash
aad826fb79b3423a764bc3c0e2e4edb2bff11f41d7c6b909643eb38fe49ff950
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/VLMCN63ZWNBDU5SLYPAOFZHNWK \
| 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: aad826fb79b3423a764bc3c0e2e4edb2bff11f41d7c6b909643eb38fe49ff950
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "0a909f7c61fad24afed9b8e1b77aad5a95b39cb5dfb74787b84071f7c6ee4952",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "stat.ME",
"submitted_at": "2023-12-23T11:05:19Z",
"title_canon_sha256": "64d16e77177dde484c16c74ff6c49075e608a265f64a38db221d12d8dadea69a"
},
"schema_version": "1.0",
"source": {
"id": "2312.15222",
"kind": "arxiv",
"version": 6
}
}