Pith Number

pith:E57WKQFE

pith:2026:E57WKQFE36RABBZUWGA2IX6FVK

not attested not anchored not stored refs pending

When PCOS Meets Eating Disorders: An Explainable AI Approach to Detecting the Hidden Triple Burden

Apoorv Prasad, Susan McRoy

Fine-tuned small language models can detect the overlapping presence of PCOS, eating disorders, and related issues in social media with built-in explanations.

arxiv:2604.14356 v2 · 2026-04-15 · cs.CL · cs.AI

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\usepackage{pith}
\pithnumber{E57WKQFE36RABBZUWGA2IX6FVK}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ 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.

Claims

C1strongest claim

The best model achieved 75.3 percent exact match accuracy on 150 held-out posts, with robust comorbidity detection and strong explainability.

C2weakest assumption

That annotations performed by two trained annotators using the Lee et al. (2017) clinical framework on Reddit posts accurately and reliably capture the presence of the triple burden, and that the resulting models generalize beyond the six sampled subreddits and the 2026 collection period.

C3one line summary

Small language models detect the triple burden of PCOS, disordered eating, and body image issues in social media posts at 75.3% exact match accuracy with grounded explanations.

Receipt and verification

First computed	2026-05-28T02:04:47.630596Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

277f6540a4dfa2008734b181a45fc5aa9d846a0fb84c38a54fd48d8d3c9f5bef

Aliases

arxiv: 2604.14356 · arxiv_version: 2604.14356v2 · doi: 10.48550/arxiv.2604.14356 · pith_short_12: E57WKQFE36RA · pith_short_16: E57WKQFE36RABBZU · pith_short_8: E57WKQFE

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/E57WKQFE36RABBZUWGA2IX6FVK \
  | 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: 277f6540a4dfa2008734b181a45fc5aa9d846a0fb84c38a54fd48d8d3c9f5bef

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "0222a49602082fb82239d677b58e63844b4cbc18b49e994979d0ef089ba050c4",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-04-15T19:18:27Z",
    "title_canon_sha256": "1c6be831913515261528e17b8316991ef71beee9bbcf1c6fcdcc6b96d71d7848"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.14356",
    "kind": "arxiv",
    "version": 2
  }
}