Pith Number
pith:7I5FGBAK
pith:2021:7I5FGBAKT4C75RR7P7V3SII5YH
not attested
not anchored
not stored
refs pending
Physics-informed generative neural network: an application to troposphere temperature prediction
arxiv:2107.06991 v1 · 2021-07-08 · cs.LG · physics.ao-ph
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{7I5FGBAKT4C75RR7P7V3SII5YH}
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
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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 | 2026-07-05T02:58:09.320275Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
fa3a53040a9f05fec63f7febb9211dc1e901f8eb833049d52a9c1b9abdf71255
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/7I5FGBAKT4C75RR7P7V3SII5YH \
| 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: fa3a53040a9f05fec63f7febb9211dc1e901f8eb833049d52a9c1b9abdf71255
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "1dd98db662cc81a7028faa1ef49eed29814117327e5fdf23a191c1b94e5ae109",
"cross_cats_sorted": [
"physics.ao-ph"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2021-07-08T09:07:07Z",
"title_canon_sha256": "e1abbbaf19c4112020916c094ed36c5abed3639d9cd0aff55650cfc0e30fcc81"
},
"schema_version": "1.0",
"source": {
"id": "2107.06991",
"kind": "arxiv",
"version": 1
}
}