Pith Number
pith:4O373LTH
pith:2018:4O373LTHA3D3E52FYSYY6TWSH4
not attested
not anchored
not stored
refs pending
A Scalable Machine Learning Approach for Inferring Probabilistic US-LI-RADS Categorization
arxiv:1806.07346 v1 · 2018-06-15 · cs.CL · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{4O373LTHA3D3E52FYSYY6TWSH4}
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 | 2026-05-18T00:12:51.264809Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
e3b7fdae6706c7b27745c4b18f4ed23f1fd3bd36ba0c1af35e3f2a02b162cd73
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/4O373LTHA3D3E52FYSYY6TWSH4 \
| 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: e3b7fdae6706c7b27745c4b18f4ed23f1fd3bd36ba0c1af35e3f2a02b162cd73
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "418c1658a5d075c6f5729be8901ae28bdcc29aceeaafa007777ee455b93d38af",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CL",
"submitted_at": "2018-06-15T20:11:22Z",
"title_canon_sha256": "ce60042503a294febc8ed6310978f4314569ced22a582a2a81530c174ae5aa46"
},
"schema_version": "1.0",
"source": {
"id": "1806.07346",
"kind": "arxiv",
"version": 1
}
}