Pith Number

pith:GCY2WGTR

pith:2025:GCY2WGTR6XYXF5SRLOXOO5JXP3

not attested not anchored not stored refs pending

Skillful joint probabilistic weather forecasting from marginals

Alvaro Sanchez-Gonzalez, Andrew El-Kadi, Dominic Masters, Ferran Alet, Ilan Price, Jacklynn Stott, Matthew Willson, Peter Battaglia, Remi Lam, Stratis Markou, Tom R. Andersson

arxiv:2506.10772 v1 · 2025-06-12 · cs.LG · physics.ao-ph

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Add to your LaTeX paper

\usepackage{pith}
\pithnumber{GCY2WGTR6XYXF5SRLOXOO5JXP3}

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 open · sign in to claim

4 Citations open

5 Replications open

✓ 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

19 papers in Pith

Evaluation of medium range machine learning models for sub-seasonal prediction

Otter Weather: Skillful and Computationally Efficient Medium-Range Weather Forecasting

Towards Fair Comparisons of AI- and Physics-Based Weather Models for Extreme Events via the Weighted Potential CRPS

Rigorous uncertainty quantification of probabilistic AI weather forecasts with conformal prediction

Reliability of Probabilistic Emulation of Physical Systems

Receipt and verification

First computed	2026-07-05T11:20:30.347834Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

30b1ab1a71f5f172f6515baee775377ef8b6450bdc4f8fae58cc869cef94f40e

Aliases

arxiv: 2506.10772 · arxiv_version: 2506.10772v1 · doi: 10.48550/arxiv.2506.10772 · pith_short_12: GCY2WGTR6XYX · pith_short_16: GCY2WGTR6XYXF5SR · pith_short_8: GCY2WGTR

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/GCY2WGTR6XYXF5SRLOXOO5JXP3 \
  | 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: 30b1ab1a71f5f172f6515baee775377ef8b6450bdc4f8fae58cc869cef94f40e

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "c6daa7ed7005fe549e9f52eaa0c41f9d221a856c22bf7ebaeac17e389cdafb07",
    "cross_cats_sorted": [
      "physics.ao-ph"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2025-06-12T14:50:47Z",
    "title_canon_sha256": "bfd83b391e44e05a913df1e2bebbeb1457a07184768c0510f020230f0e79a6fb"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2506.10772",
    "kind": "arxiv",
    "version": 1
  }
}