Pith Number
pith:Z72K3F2P
pith:2015:Z72K3F2PUE55ZV3UTK32IDPVRR
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refs pending
How much data is needed to train a medical image deep learning system to achieve necessary high accuracy?
arxiv:1511.06348 v2 · 2015-11-19 · cs.LG · cs.CV · cs.NE
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{Z72K3F2PUE55ZV3UTK32IDPVRR}
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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 | 2026-05-18T01:23:11.811058Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
cff4ad974fa13bdcd7749ab7a40df58c415b60a8f445e84a9b8fe59dd624177c
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/Z72K3F2PUE55ZV3UTK32IDPVRR \
| 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: cff4ad974fa13bdcd7749ab7a40df58c415b60a8f445e84a9b8fe59dd624177c
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "e1e7460c33c74052a96b15a7d705d8a8e0a8cb9bb62c36aac04e65ff89e6ef44",
"cross_cats_sorted": [
"cs.CV",
"cs.NE"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2015-11-19T20:38:43Z",
"title_canon_sha256": "b08dd0687c0f4da68f5f7191e87a9da8d8ce45c07fcd03a4698754ff776bf61b"
},
"schema_version": "1.0",
"source": {
"id": "1511.06348",
"kind": "arxiv",
"version": 2
}
}