Pith Number
pith:D7QLZUZD
pith:2022:D7QLZUZDD2OL5NB3FQNGR3TI34
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TgDLF2.0: Theory-guided deep-learning for electrical load forecasting via Transformer and transfer learning
arxiv:2210.02448 v1 · 2022-10-05 · cs.LG · eess.SP
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{D7QLZUZDD2OL5NB3FQNGR3TI34}
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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 | 2026-07-05T05:04:04.280051Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
1fe0bcd3231e9cbeb43b2c1a68ee68df021c34f8cc455497e2664aeca2f6a4ba
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/D7QLZUZDD2OL5NB3FQNGR3TI34 \
| 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: 1fe0bcd3231e9cbeb43b2c1a68ee68df021c34f8cc455497e2664aeca2f6a4ba
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "5ddacb34ca4158c07964a2ea95452c9eed824f4bf28ae140ef8bac3d90c0f8f6",
"cross_cats_sorted": [
"eess.SP"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2022-10-05T04:12:50Z",
"title_canon_sha256": "860be890811bca8535c2148fee9ef7240a2cfd07e0c91e4566f8b1e0556939b6"
},
"schema_version": "1.0",
"source": {
"id": "2210.02448",
"kind": "arxiv",
"version": 1
}
}