Pith Number
pith:ORHJJHQL
pith:2026:ORHJJHQL7BDI24P3KMSRG4YR6F
not attested
not anchored
not stored
refs pending
Curia-MAE: Multi-Modal Multi-Anatomy MAE Pre-Training for 3D Medical Image Segmentation
arxiv:2608.05844 v1 · 2026-08-06 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ORHJJHQL7BDI24P3KMSRG4YR6F}
Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge
Record completeness
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Bitcoin timestamp
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Internet Archive
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4
Citations
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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 | 2026-08-07T00:52:52.455076Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
744e949e0bf8468d71fb5325137311f165a3b63a285cb008751ebf16e0bf2c92
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ORHJJHQL7BDI24P3KMSRG4YR6F \
| 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: 744e949e0bf8468d71fb5325137311f165a3b63a285cb008751ebf16e0bf2c92
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "6b6717b9c96e15f1167dc0dec65400af4565c493755a9d43edda5728c8cdb0b8",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "cs.CV",
"submitted_at": "2026-08-06T10:17:23Z",
"title_canon_sha256": "4064baca91809f520a4c3fb2c9866fc18308c29cd5d428ff51f33fd340f88c42"
},
"schema_version": "1.0",
"source": {
"id": "2608.05844",
"kind": "arxiv",
"version": 1
}
}