Pith Number
pith:GLBUNLQ7
pith:2024:GLBUNLQ7A5PRW56CN4FJEIUARU
not attested
not anchored
not stored
refs pending
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach
arxiv:2402.03750 v1 · 2024-02-06 · cs.LG · cs.AI · cs.HC
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{GLBUNLQ7A5PRW56CN4FJEIUARU}
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 | 2026-07-05T07:41:57.902868Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
32c346ae1f075f1b77c26f0a9222808d25d9a5579d6b9d0397eb689ab5d367a7
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GLBUNLQ7A5PRW56CN4FJEIUARU \
| 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: 32c346ae1f075f1b77c26f0a9222808d25d9a5579d6b9d0397eb689ab5d367a7
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "8edccc0d5ebbfaa243a6c174b9113bc0eef58d1de08a10a76fcc065d8d665564",
"cross_cats_sorted": [
"cs.AI",
"cs.HC"
],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-02-06T06:37:43Z",
"title_canon_sha256": "74dba88c8a26be71a6a993531227d7c7c6f4c5d7841a69dcbc6949796478e782"
},
"schema_version": "1.0",
"source": {
"id": "2402.03750",
"kind": "arxiv",
"version": 1
}
}