Pith Number
pith:JCSABVUW
pith:2022:JCSABVUWJDWWA7M2BCODMLUQU4
not attested
not anchored
not stored
refs pending
Understanding of the properties of neural network approaches for transient light curve approximations
arxiv:2209.07542 v2 · 2022-09-15 · astro-ph.IM · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JCSABVUWJDWWA7M2BCODMLUQU4}
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 | 2026-07-05T06:51:19.522769Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
48a400d69648ed607d9a089c362e90a711539ae142c83d243006cf6fdccec366
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JCSABVUWJDWWA7M2BCODMLUQU4 \
| 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: 48a400d69648ed607d9a089c362e90a711539ae142c83d243006cf6fdccec366
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "196bf9ffef65aa5ae95a0a89448f27f28fef2297243185e4f5764c7c710c3f0d",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "astro-ph.IM",
"submitted_at": "2022-09-15T18:00:08Z",
"title_canon_sha256": "5eb17a66c578a1e3c82f016403c62d5e60ade8b3541f85e5014f15f4f0b00549"
},
"schema_version": "1.0",
"source": {
"id": "2209.07542",
"kind": "arxiv",
"version": 2
}
}