Pith Number
pith:RIH6VCAM
pith:2018:RIH6VCAM4MTXUXTYDRTQX3UUML
not attested
not anchored
not stored
refs pending
Automated soft tissue lesion detection and segmentation in digital mammography using a u-net deep learning network
arxiv:1802.06865 v2 · 2018-02-19 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{RIH6VCAM4MTXUXTYDRTQX3UUML}
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 | 2026-05-18T00:21:45.563340Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
8a0fea880ce3277a5e781c670bee9462d752571902dd0a1677dcddc95836fe4e
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/RIH6VCAM4MTXUXTYDRTQX3UUML \
| 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: 8a0fea880ce3277a5e781c670bee9462d752571902dd0a1677dcddc95836fe4e
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "5598f2f5176651d4d6fce541fd7d8632e622f193113232572f64c2fddc64b96c",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2018-02-19T21:39:49Z",
"title_canon_sha256": "fde51b79dd9319789e6904b52175ad227561fd98b97404822a296f7dae950f2b"
},
"schema_version": "1.0",
"source": {
"id": "1802.06865",
"kind": "arxiv",
"version": 2
}
}