Pith Number
pith:67OUPWCX
pith:2019:67OUPWCXXQUS535H7EM2CEQJ22
not attested
not anchored
not stored
refs pending
Magnetic Resonance Fingerprinting Reconstruction Using Recurrent Neural Networks
arxiv:1909.06395 v1 · 2019-09-13 · eess.IV · cs.CV
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{67OUPWCXXQUS535H7EM2CEQJ22}
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 | 2026-07-05T00:04:45.789941Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
f7dd47d857bc292eefa7f919a11209d690048462cd49691a7f0bc058d1bf8c29
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/67OUPWCXXQUS535H7EM2CEQJ22 \
| 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: f7dd47d857bc292eefa7f919a11209d690048462cd49691a7f0bc058d1bf8c29
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "8ee623f3efde2c5ee304023ea167ee49cb02ce16d3604b976d84f2b105d63eef",
"cross_cats_sorted": [
"cs.CV"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "eess.IV",
"submitted_at": "2019-09-13T18:17:19Z",
"title_canon_sha256": "9c5c1f22d2e437bc4ef387220932347e8ce793a9c200d5f6a25f238eeba096bd"
},
"schema_version": "1.0",
"source": {
"id": "1909.06395",
"kind": "arxiv",
"version": 1
}
}