Pith Number
pith:MQOFNC4A
pith:2023:MQOFNC4AOWDJIRKVBBWZ6AZCKD
not attested
not anchored
not stored
refs pending
Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation
arxiv:2303.16507 v1 · 2023-03-29 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{MQOFNC4AOWDJIRKVBBWZ6AZCKD}
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 | 2026-07-05T05:56:07.716358Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
641c568b807586944555086d9f032250fe78359b500053f79e852b4b85dc96d3
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MQOFNC4AOWDJIRKVBBWZ6AZCKD \
| 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: 641c568b807586944555086d9f032250fe78359b500053f79e852b4b85dc96d3
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "ca6171c9c80bce6e61459c79df8214deacfa408dc759d8edac92522d0f8a7f67",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2023-03-29T07:34:20Z",
"title_canon_sha256": "7f6b6483c2f6b6b9d5d3f33780f1b296838eaa0142c8ba0035ce4a174eb02bc5"
},
"schema_version": "1.0",
"source": {
"id": "2303.16507",
"kind": "arxiv",
"version": 1
}
}