Pith Number
pith:2JZ2JL2W
pith:2018:2JZ2JL2WYKPLU6C2C7Y4AMQTD7
not attested
not anchored
not stored
refs pending
Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising
arxiv:1805.00587 v3 · 2018-05-02 · cs.CV · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{2JZ2JL2WYKPLU6C2C7Y4AMQTD7}
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 | 2026-05-18T00:08:25.495240Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d273a4af56c29eba785a17f1c032131fc98b6b72c959070e2b57f5569ab97420
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/2JZ2JL2WYKPLU6C2C7Y4AMQTD7 \
| 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: d273a4af56c29eba785a17f1c032131fc98b6b72c959070e2b57f5569ab97420
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "5f4cc636df4bf2c229a09935ff92f0d4e21f7c1cd50b1be2773749c99749010e",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2018-05-02T00:37:05Z",
"title_canon_sha256": "784c8ed835a6f57b28fda7819f83a1a492f1ef1e189ca7569de79817f41ee4da"
},
"schema_version": "1.0",
"source": {
"id": "1805.00587",
"kind": "arxiv",
"version": 3
}
}