Pith Number
pith:JG6JECQU
pith:2024:JG6JECQU4MJZMPT2NFERO7FWVV
not attested
not anchored
not stored
refs pending
A Scalable Bayesian Spatiotemporal Model for Water Level Predictions using a Nearest Neighbor Gaussian Process Approach
arxiv:2412.06934 v3 · 2024-12-09 · stat.AP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JG6JECQU4MJZMPT2NFERO7FWVV}
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 | 2026-06-23T02:12:31.089740Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
49bc920a14e313963e7a6949177cb6ad454c1689555a1ae32d9e0552c0d5fde8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JG6JECQU4MJZMPT2NFERO7FWVV \
| 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: 49bc920a14e313963e7a6949177cb6ad454c1689555a1ae32d9e0552c0d5fde8
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "f36b5d9ecd819c74b478d2abe1e98a238c0bfd0f441396ad1fb2fe197daf340b",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "stat.AP",
"submitted_at": "2024-12-09T19:24:18Z",
"title_canon_sha256": "cc3d7ebf5caef5cd81af54c3e268b1cd225e3618ce4a2c66767393b0f9b2f80f"
},
"schema_version": "1.0",
"source": {
"id": "2412.06934",
"kind": "arxiv",
"version": 3
}
}