Pith Number
pith:T7NGQFGI
pith:2022:T7NGQFGIH3O2WAE57OOSMVIIG5
not attested
not anchored
not stored
refs pending
Bias and unfairness in machine learning models: a systematic literature review
arxiv:2202.08176 v4 · 2022-02-16 · cs.LG · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{T7NGQFGIH3O2WAE57OOSMVIIG5}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T05:12:50.137590Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
9fda6814c83eddab009dfb9d2655083741e70b422c7ec7acdf7e25f2f3a2c521
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/T7NGQFGIH3O2WAE57OOSMVIIG5 \
| 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: 9fda6814c83eddab009dfb9d2655083741e70b422c7ec7acdf7e25f2f3a2c521
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "8302a427875d5648fcf336d62aced9f2cdb7b89d5303aa9d4bc9192383def94a",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-02-16T16:27:00Z",
"title_canon_sha256": "bd2512ad700c0938da6b02d6f80782158d7f5c3575177bb258caa107f165f8ec"
},
"schema_version": "1.0",
"source": {
"id": "2202.08176",
"kind": "arxiv",
"version": 4
}
}