Pith Number
pith:GVFTL2IP
pith:2025:GVFTL2IPGPY6DGQ3FTH3QJA2FT
not attested
not anchored
not stored
refs pending
Enhanced Drought Analysis in Bangladesh: A Machine Learning Approach for Severity Classification Using Satellite Data
arxiv:2506.04696 v1 · 2025-06-05 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{GVFTL2IPGPY6DGQ3FTH3QJA2FT}
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
· sign in to
claim
4
Citations
5
Replications
✓
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 | 2026-07-05T11:16:18.949701Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
354b35e90f33f1e19a1b2ccfb8241a2cd85f736dc1ff04ba9b31ccce7e8519be
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/GVFTL2IPGPY6DGQ3FTH3QJA2FT \
| 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: 354b35e90f33f1e19a1b2ccfb8241a2cd85f736dc1ff04ba9b31ccce7e8519be
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "7ca59c2310ccfc22fa716abcdef0b46f355e720c158a05c6798dda2b91247831",
"cross_cats_sorted": [],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-06-05T07:17:43Z",
"title_canon_sha256": "68878404ac26b6430172a5f0de00fdf29812df3dfad4829e7e51e2a28471d26d"
},
"schema_version": "1.0",
"source": {
"id": "2506.04696",
"kind": "arxiv",
"version": 1
}
}