Pith Number
pith:MTPH3WKW
pith:2024:MTPH3WKWRK6EI54RKQLBBN2LD7
not attested
not anchored
not stored
refs pending
An Evidential-enhanced Tri-Branch Consistency Learning Method for Semi-supervised Medical Image Segmentation
arxiv:2404.07032 v1 · 2024-04-10 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{MTPH3WKWRK6EI54RKQLBBN2LD7}
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 | 2026-07-05T08:06:34.202914Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
64de7dd9568abc447791541610b74b1fcca0062378fd578c76f2a9a7f24e1b97
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MTPH3WKWRK6EI54RKQLBBN2LD7 \
| 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: 64de7dd9568abc447791541610b74b1fcca0062378fd578c76f2a9a7f24e1b97
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "ed6500b702a755ca31817b82370b2453ac4078aa8b20c3fd3a01fd3a6fc58423",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2024-04-10T14:25:23Z",
"title_canon_sha256": "2035d78b225744767715211b5827e78a5c668c1b914c6275f17c53b85dd18190"
},
"schema_version": "1.0",
"source": {
"id": "2404.07032",
"kind": "arxiv",
"version": 1
}
}