Pith Number
pith:NFNR6JRD
pith:2025:NFNR6JRDCF54TQ5SHXWTES35Y2
not attested
not anchored
not stored
refs pending
Interpretable Deep Learning Paradigm for Airborne Transient Electromagnetic Inversion
arxiv:2503.22214 v1 · 2025-03-28 · cs.LG
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{NFNR6JRDCF54TQ5SHXWTES35Y2}
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.
Cited by
Receipt and verification
| First computed | 2026-07-05T10:40:49.494238Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
695b1f2623117bc9c3b23ded324b7dc68d62919888d92210c64e8642567ab3c6
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NFNR6JRDCF54TQ5SHXWTES35Y2 \
| 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: 695b1f2623117bc9c3b23ded324b7dc68d62919888d92210c64e8642567ab3c6
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "cdbc8f72de875d2c58652ecbc8d33ea708f138b346576246b32ebc49dc41c5e8",
"cross_cats_sorted": [],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-03-28T08:01:20Z",
"title_canon_sha256": "866eca06eaf1a6b2be3cc599c4d1d4eac5015f15e34e78a106df9b596eb4f8cb"
},
"schema_version": "1.0",
"source": {
"id": "2503.22214",
"kind": "arxiv",
"version": 1
}
}