Pith Number
pith:ID4BR5CT
pith:2019:ID4BR5CTDUVJVDPW2K6AIXSMH3
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Which practical interventions does the do-operator refer to in causal inference? Illustration on the example of obesity and cancer
arxiv:1901.00772 v1 · 2019-01-03 · stat.ME
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{ID4BR5CTDUVJVDPW2K6AIXSMH3}
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Record completeness
1
Bitcoin timestamp
2
Internet Archive
3
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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 | 2026-05-17T23:57:01.302678Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
40f818f4531d2a9a8df6d2bc045e4c3ec7dfca39bf85f8d6e174b9e63cea76c0
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ID4BR5CTDUVJVDPW2K6AIXSMH3 \
| 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: 40f818f4531d2a9a8df6d2bc045e4c3ec7dfca39bf85f8d6e174b9e63cea76c0
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "92c135f9291642de803f9c1e11d2110582ff0640b5f50bb85f1fc3381f4fe2de",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "stat.ME",
"submitted_at": "2019-01-03T14:40:18Z",
"title_canon_sha256": "ade59054f2eb598c23465111b8188041dda411e484a54ac07603468f1b86377f"
},
"schema_version": "1.0",
"source": {
"id": "1901.00772",
"kind": "arxiv",
"version": 1
}
}