Pith Number
pith:JHKXVPA3
pith:2020:JHKXVPA3CKYU6WAEJYRGZLGE6P
not attested
not anchored
not stored
refs pending
Dense Forecasting of Wildfire Smoke Particulate Matter Using Sparsity Invariant Convolutional Neural Networks
arxiv:2009.11362 v1 · 2020-09-23 · cs.CV · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{JHKXVPA3CKYU6WAEJYRGZLGE6P}
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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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 | 2026-07-05T01:37:45.016610Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
49d57abc1b12b14f58044e226cacc4f3f223dcfa956f09bf2f69ae3a7155d96d
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/JHKXVPA3CKYU6WAEJYRGZLGE6P \
| 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: 49d57abc1b12b14f58044e226cacc4f3f223dcfa956f09bf2f69ae3a7155d96d
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "55665260edac6b2ba01b28ab076f2b29c5a8af47e007962c6dabf6045d0c05bb",
"cross_cats_sorted": [
"cs.LG"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CV",
"submitted_at": "2020-09-23T20:13:35Z",
"title_canon_sha256": "3612616b814587280a70cef40083c20793daf77d3829d87ecdfbe1b3a8574213"
},
"schema_version": "1.0",
"source": {
"id": "2009.11362",
"kind": "arxiv",
"version": 1
}
}