Pith Number
pith:OQM4BTHF
pith:2016:OQM4BTHFWW4WK3ZBIAQEUPN3PQ
not attested
not anchored
not stored
refs pending
ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models
arxiv:1601.03797 v1 · 2016-01-15 · cs.DB · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{OQM4BTHFWW4WK3ZBIAQEUPN3PQ}
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
· sign in to
claim
4
Citations
5
Replications
✓
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 | 2026-05-18T01:22:50.019232Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
7419c0cce5b5b9656f2140204a3dbb7c1b9ac26d8e8ac0d5bb190a1d0105ba10
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OQM4BTHFWW4WK3ZBIAQEUPN3PQ \
| 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: 7419c0cce5b5b9656f2140204a3dbb7c1b9ac26d8e8ac0d5bb190a1d0105ba10
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "6b3023d229fd87098103839a97a33a4e241ec5d4c2e652c670fe920a4139f7dc",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.DB",
"submitted_at": "2016-01-15T02:02:00Z",
"title_canon_sha256": "63c5d725d48842682241c6545ab2011e6b4b14095aed406f53ddcfcede55281a"
},
"schema_version": "1.0",
"source": {
"id": "1601.03797",
"kind": "arxiv",
"version": 1
}
}