Pith Number
pith:I5P4WB5B
pith:2025:I5P4WB5BHWGNV76VRFHGSEMJQU
not attested
not anchored
not stored
refs pending
Explainable AI for Mental Health Emergency Returns: Integrating LLMs with Predictive Modeling
arxiv:2502.00025 v4 · 2025-01-21 · cs.LG · cs.AI · cs.CY
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{I5P4WB5BHWGNV76VRFHGSEMJQU}
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 | 2026-07-05T11:32:24.034474Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
475fcb07a13d8cdaffd5894e69118985084e5554a8c5799d3dd8c91f733f3e65
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/I5P4WB5BHWGNV76VRFHGSEMJQU \
| 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: 475fcb07a13d8cdaffd5894e69118985084e5554a8c5799d3dd8c91f733f3e65
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "06ca702e41730120351c3ac3c72ca4ae62a30c02e322312aba6a8964c29e3e60",
"cross_cats_sorted": [
"cs.AI",
"cs.CY"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.LG",
"submitted_at": "2025-01-21T15:41:20Z",
"title_canon_sha256": "096305f34ec5ec7333f7e168f95762c57604ac091accda224d52f2e67022c631"
},
"schema_version": "1.0",
"source": {
"id": "2502.00025",
"kind": "arxiv",
"version": 4
}
}