Pith Number
pith:LOCKSSTZ
pith:2018:LOCKSSTZ2INECFOGDRBP3MMY3R
not attested
not anchored
not stored
refs pending
Patch-based Fake Fingerprint Detection Using a Fully Convolutional Neural Network with a Small Number of Parameters and an Optimal Threshold
arxiv:1803.07817 v1 · 2018-03-21 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{LOCKSSTZ2INECFOGDRBP3MMY3R}
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 | 2026-05-18T00:20:28.844277Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
5b84a94a79d21a4115c61c42fdb198dc4af01ca2947f38e89bac2f105316d8ce
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/LOCKSSTZ2INECFOGDRBP3MMY3R \
| 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: 5b84a94a79d21a4115c61c42fdb198dc4af01ca2947f38e89bac2f105316d8ce
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "48871c1aebdef3339a717727e4e5ec3e307b73fb3d8195947b5fbecdb9326ba9",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2018-03-21T09:50:25Z",
"title_canon_sha256": "d09c5e0715818704bc9209873a735f4c05663cd655cc2a813449d998a95ad16a"
},
"schema_version": "1.0",
"source": {
"id": "1803.07817",
"kind": "arxiv",
"version": 1
}
}