Pith Number
pith:AMQPPDNQ
pith:2021:AMQPPDNQ5P3NYJDNC6HBACJJ7U
not attested
not anchored
not stored
refs pending
Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction models
arxiv:2102.05107 v1 · 2021-02-09 · physics.ao-ph · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{AMQPPDNQ5P3NYJDNC6HBACJJ7U}
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 | 2026-07-05T03:39:13.261033Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
0320f78db0ebf6dc246d178e100929fd0d2e15252464414f59b223efd8b904ea
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/AMQPPDNQ5P3NYJDNC6HBACJJ7U \
| 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: 0320f78db0ebf6dc246d178e100929fd0d2e15252464414f59b223efd8b904ea
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "c5cd23597fe04dd6d735e4aef7e49ed19fed2915c1e483bba8d6358186ecda28",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "physics.ao-ph",
"submitted_at": "2021-02-09T20:14:43Z",
"title_canon_sha256": "5159a257ca4f08a4117d9ff348f3061ae382b323e9fe900964ba7c1d48082821"
},
"schema_version": "1.0",
"source": {
"id": "2102.05107",
"kind": "arxiv",
"version": 1
}
}