Pith Number
pith:ACWEZZMS
pith:2021:ACWEZZMSA7AQDHAT2OGROVTF7H
not attested
not anchored
not stored
refs pending
Subtle Data Crimes: Naively training machine learning algorithms could lead to overly-optimistic results
arxiv:2109.08237 v3 · 2021-09-16 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ACWEZZMSA7AQDHAT2OGROVTF7H}
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 | 2026-07-05T03:40:46.407697Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
00ac4ce59207c1019c13d38d175665f9c848436cc61609a5afba8bfcb31769ee
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ACWEZZMSA7AQDHAT2OGROVTF7H \
| 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: 00ac4ce59207c1019c13d38d175665f9c848436cc61609a5afba8bfcb31769ee
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c1d838304af79ce8b6ad48f189e1d5e0baa559b2898a0cb5620b10142c7e7cb7",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2021-09-16T22:00:15Z",
"title_canon_sha256": "e2b64364436f90d2b583a889720d5e43b7268e7fcf429969999ffb85ae5d01d8"
},
"schema_version": "1.0",
"source": {
"id": "2109.08237",
"kind": "arxiv",
"version": 3
}
}