Pith Number
pith:ECTE5INX
pith:2022:ECTE5INXDHCH4OKOALB6DYLSYS
not attested
not anchored
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refs pending
What does a deep neural network confidently perceive? The effective dimension of high certainty class manifolds and their low confidence boundaries
arxiv:2210.05546 v1 · 2022-10-11 · cs.LG · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ECTE5INXDHCH4OKOALB6DYLSYS}
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Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
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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 | 2026-07-05T05:05:17.882069Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
20a64ea1b719c47e394e02c3e1e172c4b7f2540de7925d1d750bfb01d4fdcf55
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ECTE5INXDHCH4OKOALB6DYLSYS \
| 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: 20a64ea1b719c47e394e02c3e1e172c4b7f2540de7925d1d750bfb01d4fdcf55
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "aaaeb964b0318a14609986986130dd0530cd6bc3385a7dd2b9b4aaf433bef8cb",
"cross_cats_sorted": [
"cs.CV"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-10-11T15:42:06Z",
"title_canon_sha256": "0269b5cb94a66f217680fe08d59215a2c354cdb068b775b6d97cc43b03f04e9b"
},
"schema_version": "1.0",
"source": {
"id": "2210.05546",
"kind": "arxiv",
"version": 1
}
}