Pith Number
pith:OCR7MLA4
pith:2025:OCR7MLA4ZGFBBRVQIIGE7QIRN6
not attested
not anchored
not stored
refs pending
MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis
arxiv:2505.00032 v1 · 2025-04-28 · cs.CL · cs.AI
Add to your LaTeX paper
\usepackage{pith}
\pithnumber{OCR7MLA4ZGFBBRVQIIGE7QIRN6}
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 | 2026-07-05T10:56:40.799398Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
70a3f62c1cc98a10c6b0420c4fc1116fb574ce142e6ca18f76aa451df9e332c1
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OCR7MLA4ZGFBBRVQIIGE7QIRN6 \
| 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: 70a3f62c1cc98a10c6b0420c4fc1116fb574ce142e6ca18f76aa451df9e332c1
Canonical record JSON
{
"metadata": {
"abstract_canon_sha256": "806c0c4ba6b5c8d2cc730b07923b91adb057066f66201876d0c18dbab9346b6d",
"cross_cats_sorted": [
"cs.AI"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"primary_cat": "cs.CL",
"submitted_at": "2025-04-28T08:53:55Z",
"title_canon_sha256": "89ce0928c4987d63cc8b986b735ce86f1b3e71f018289b015dea4c75e7f08e1c"
},
"schema_version": "1.0",
"source": {
"id": "2505.00032",
"kind": "arxiv",
"version": 1
}
}