Pith Number
pith:GVTZMQBK
pith:2019:GVTZMQBKDB2VYHOY3YURMVSDNM
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Measurement of Anomalous Diffusion Using Recurrent Neural Networks
arxiv:1905.02038 v2 · 2019-05-06 · cond-mat.stat-mech
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{GVTZMQBKDB2VYHOY3YURMVSDNM}
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Record completeness
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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 | 2026-05-17T23:39:43.812519Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
356796402a18755c1dd8de291656436b0a47a31847bb49a4fabb6e8a7b9bcc52
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GVTZMQBKDB2VYHOY3YURMVSDNM \
| 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: 356796402a18755c1dd8de291656436b0a47a31847bb49a4fabb6e8a7b9bcc52
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "04c12f5bb234f28f3d6518ef3cb18d5fed48a1eb57bff0d8927eefd31bb20d17",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cond-mat.stat-mech",
"submitted_at": "2019-05-06T13:35:38Z",
"title_canon_sha256": "cf27d273441810afd8f9e7231a2e93c4373864a3f796baa5697b3056a7336629"
},
"schema_version": "1.0",
"source": {
"id": "1905.02038",
"kind": "arxiv",
"version": 2
}
}