Pith Number
pith:EWUGNPFQ
pith:2022:EWUGNPFQ3ALPE3YEPNEVOCV3UA
not attested
not anchored
not stored
refs pending
Can Ensembling Pre-processing Algorithms Lead to Better Machine Learning Fairness?
arxiv:2212.02614 v1 · 2022-12-05 · cs.LG · cs.AI · cs.CY
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{EWUGNPFQ3ALPE3YEPNEVOCV3UA}
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 | 2026-07-05T05:22:32.743636Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
25a866bcb0d816f26f047b49570abba0065f140fff27996c652f19221fd04510
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/EWUGNPFQ3ALPE3YEPNEVOCV3UA \
| 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: 25a866bcb0d816f26f047b49570abba0065f140fff27996c652f19221fd04510
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "4365b848f064a9c9ccdd7164110254fcfaff1358b586287ac783d48e3fe4c8ce",
"cross_cats_sorted": [
"cs.AI",
"cs.CY"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-12-05T21:54:29Z",
"title_canon_sha256": "6e11213d7bad1408b45ac229afc1d496d977aabcec534852fa31b8159a131b08"
},
"schema_version": "1.0",
"source": {
"id": "2212.02614",
"kind": "arxiv",
"version": 1
}
}