Pith Number
pith:FSLE4KJ2
pith:2017:FSLE4KJ2KOIXAWHWM7KK2D6I5C
not attested
not anchored
not stored
refs pending
Detection-aided liver lesion segmentation using deep learning
arxiv:1711.11069 v1 · 2017-11-29 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{FSLE4KJ2KOIXAWHWM7KK2D6I5C}
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
· sign in to
claim
4
Citations
5
Replications
✓
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 | 2026-05-18T00:29:12.580784Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
2c964e293a53917058f667d4ad0fc8e8a20f34a2c108fabe66f8013868f97b5a
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/FSLE4KJ2KOIXAWHWM7KK2D6I5C \
| 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: 2c964e293a53917058f667d4ad0fc8e8a20f34a2c108fabe66f8013868f97b5a
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "ebcfba3b4d5fbf3f4c17edd8a2ec237eac176d0c59fdeed29820ce34a91491bb",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2017-11-29T19:27:40Z",
"title_canon_sha256": "1f1926e029c72b2058e8992aaf61c11bdfaa22c01a8acdab7f0974ac6b03c366"
},
"schema_version": "1.0",
"source": {
"id": "1711.11069",
"kind": "arxiv",
"version": 1
}
}