Pith Number
pith:WGPRS24J
pith:2017:WGPRS24JE4CK22X43CB2IBVYZ2
not attested
not anchored
not stored
refs pending
Evaluating race and sex diversity in the world's largest companies using deep neural networks
arxiv:1707.02353 v1 · 2017-07-09 · cs.CY · cs.AI · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{WGPRS24JE4CK22X43CB2IBVYZ2}
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 | 2026-05-18T00:40:39.439738Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b19f196b892704ad6afcd883a406b8cea32b6b9253b0ecc6c8bc6e2dcd824df7
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WGPRS24JE4CK22X43CB2IBVYZ2 \
| 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: b19f196b892704ad6afcd883a406b8cea32b6b9253b0ecc6c8bc6e2dcd824df7
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "26488350baf1e8024b0f938805027be4f177fdb77ea6a41b0f8d5fab5ba16a2f",
"cross_cats_sorted": [
"cs.AI",
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CY",
"submitted_at": "2017-07-09T12:32:19Z",
"title_canon_sha256": "6cb42c9e19b05af15b3ac60eecd9bdd63cf2e2cd0d7ad106576930ea4b075933"
},
"schema_version": "1.0",
"source": {
"id": "1707.02353",
"kind": "arxiv",
"version": 1
}
}