Pith Number
pith:QYXWJLDF
pith:2019:QYXWJLDF4XNLJGWZ3V7WAY5IDT
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not stored
refs pending
Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression
arxiv:1910.03783 v1 · 2019-10-09 · cs.LG · stat.ML
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{QYXWJLDF4XNLJGWZ3V7WAY5IDT}
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 | 2026-07-05T00:10:57.919549Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
862f64ac65e5dab49ad9dd7f6063a81cfbd12a61be43e588c28d9ef8abea3e00
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QYXWJLDF4XNLJGWZ3V7WAY5IDT \
| 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: 862f64ac65e5dab49ad9dd7f6063a81cfbd12a61be43e588c28d9ef8abea3e00
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "437253c4385b227b752c8ed9b4bd6dfaef897debeb990e1b63032b0a91ebba2f",
"cross_cats_sorted": [
"stat.ML"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2019-10-09T04:13:51Z",
"title_canon_sha256": "2512c3e0f0ee1fabb7d6eea6a4f7b45fd9843ff62440f163a6e024c75a69e486"
},
"schema_version": "1.0",
"source": {
"id": "1910.03783",
"kind": "arxiv",
"version": 1
}
}