Pith Number
pith:OLAXEOCR
pith:2025:OLAXEOCRQLOFBYDJITQFUJVIAH
not attested
not anchored
not stored
refs pending
FreqDGT: Frequency-Adaptive Dynamic Graph Networks with Transformer for Cross-subject EEG Emotion Recognition
arxiv:2506.22807 v3 · 2025-06-28 · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{OLAXEOCRQLOFBYDJITQFUJVIAH}
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 | 2026-07-05T11:55:40.980962Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
72c172385182dc50e06944e05a26a801f108ca299f2e7bfb0b0ec81caadd6b3e
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OLAXEOCRQLOFBYDJITQFUJVIAH \
| 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: 72c172385182dc50e06944e05a26a801f108ca299f2e7bfb0b0ec81caadd6b3e
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "894db966f5f3e16b4d2bd04767874e0a32dcca802a11c433999081ed650bb044",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2025-06-28T08:18:05Z",
"title_canon_sha256": "db41e2f6ae4c34f070e0e0cecb4537388277c83268707b0a231210c8e40cb2e6"
},
"schema_version": "1.0",
"source": {
"id": "2506.22807",
"kind": "arxiv",
"version": 3
}
}