Pith Number
pith:OPGX55UD
pith:2017:OPGX55UD6XOR7H6A4OV6FUFKX5
not attested
not anchored
not stored
refs pending
Unsupervised temporal context learning using convolutional neural networks for laparoscopic workflow analysis
arxiv:1702.03684 v1 · 2017-02-13 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{OPGX55UD6XOR7H6A4OV6FUFKX5}
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 | 2026-05-18T00:50:53.252015Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
73cd7ef683f5dd1f9fc0e3abe2d0aabf49fe328b51c4a4bdd3c082a27e5bdb2c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OPGX55UD6XOR7H6A4OV6FUFKX5 \
| 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: 73cd7ef683f5dd1f9fc0e3abe2d0aabf49fe328b51c4a4bdd3c082a27e5bdb2c
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "10e411e90f04284c4c7c86a9311b7aece94b965f7802aebb3d3daf00d9601d09",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2017-02-13T09:29:50Z",
"title_canon_sha256": "9f3d578aa1f5cf66f63ee42fa9e688488c0a480ac0f7c771dede25418e11caf6"
},
"schema_version": "1.0",
"source": {
"id": "1702.03684",
"kind": "arxiv",
"version": 1
}
}