Pith Number
pith:JMGDMQB3
pith:2024:JMGDMQB3G674IW3GVHD7LWPROT
not attested
not anchored
not stored
refs pending
An evidential time-to-event prediction model based on Gaussian random fuzzy numbers
arxiv:2406.13487 v1 · 2024-06-19 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JMGDMQB3G674IW3GVHD7LWPROT}
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 | 2026-07-05T08:34:30.665632Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4b0c36403b37bfc45b66a9c7f5d9f174df81082c4d412b1b1f75791b81a24ae7
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JMGDMQB3G674IW3GVHD7LWPROT \
| 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: 4b0c36403b37bfc45b66a9c7f5d9f174df81082c4d412b1b1f75791b81a24ae7
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "9b9a3f16f27361af0fa19ddb02eaa59a0da1f853f6b7406b7b149d340735dccf",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2024-06-19T12:14:45Z",
"title_canon_sha256": "37e3972a028fda1ee0334bfb6ab713051e2e34bfb217eabbd691e65416d39843"
},
"schema_version": "1.0",
"source": {
"id": "2406.13487",
"kind": "arxiv",
"version": 1
}
}