Pith Number
pith:FRYPRMPL
pith:2024:FRYPRMPLZQIWODDK26HSWFN4Q3
not attested
not anchored
not stored
refs pending
Uncertainty-aware Evidential Fusion-based Learning for Semi-supervised Medical Image Segmentation
arxiv:2404.06177 v2 · 2024-04-09 · cs.CV · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{FRYPRMPLZQIWODDK26HSWFN4Q3}
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 | 2026-07-05T08:06:48.765042Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
2c70f8b1ebcc11670c6ad78f2b15bc86df6aa7b2bf307efe4852e7b3e97a3fd1
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/FRYPRMPLZQIWODDK26HSWFN4Q3 \
| 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: 2c70f8b1ebcc11670c6ad78f2b15bc86df6aa7b2bf307efe4852e7b3e97a3fd1
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "578e5ff153a1d13d25961c30187352f22ab9ed9522e0f5cfb316a7ba8f5fc4c0",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2024-04-09T09:58:10Z",
"title_canon_sha256": "28c48d8c8d906e2eaedf491b7f7225418b2636105dfd4ce3fb4330023f7210a2"
},
"schema_version": "1.0",
"source": {
"id": "2404.06177",
"kind": "arxiv",
"version": 2
}
}