Pith Number
pith:B5UV2SYQ
pith:2025:B5UV2SYQ3F22L673AVILE6GQ5R
not attested
not anchored
not stored
refs pending
Characterization of Fractal Basins Using Deep Convolutional Neural Networks
arxiv:2501.17603 v1 · 2025-01-29 · nlin.CD
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{B5UV2SYQ3F22L673AVILE6GQ5R}
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 | 2026-07-05T10:06:55.633368Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
0f695d4b10d975a5fbfb0550b278d0ec62a0a37867959ace0b91b44be871487d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/B5UV2SYQ3F22L673AVILE6GQ5R \
| 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: 0f695d4b10d975a5fbfb0550b278d0ec62a0a37867959ace0b91b44be871487d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "4c4c70d6d6c0c15cd40c4e215c4556b232f905a2f9613a1610e5438b27bb9fad",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "nlin.CD",
"submitted_at": "2025-01-29T12:17:33Z",
"title_canon_sha256": "20d24c0d73ce2b03af386106e1c0e4df916ba3ab98433074ec37cf0ea9935b30"
},
"schema_version": "1.0",
"source": {
"id": "2501.17603",
"kind": "arxiv",
"version": 1
}
}