Pith Number
pith:BZI657TD
pith:2017:BZI657TDWHHO37VGKK6OJJZQPV
not attested
not anchored
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refs pending
Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding
arxiv:1701.07474 v1 · 2017-01-25 · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{BZI657TDWHHO37VGKK6OJJZQPV}
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 | 2026-05-18T00:52:03.389121Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
0e51eefe63b1ceedfea652bce4a7307d4c8b4657dc4e6cd5888e8c6145a5f1be
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/BZI657TDWHHO37VGKK6OJJZQPV \
| 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: 0e51eefe63b1ceedfea652bce4a7307d4c8b4657dc4e6cd5888e8c6145a5f1be
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "37e1a10a3887ce78e0e569f0ae8c4f5f22d9fc3d1a9e8ce2018387733b44a7c9",
"cross_cats_sorted": [
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2017-01-25T20:25:29Z",
"title_canon_sha256": "d8e38a74defd9dee68c030bc6062b92f1a02319730456d9100815ff9aa778a22"
},
"schema_version": "1.0",
"source": {
"id": "1701.07474",
"kind": "arxiv",
"version": 1
}
}