The mSCOFF for Screening Disordered Eating in Pediatric Type 1 Diabetes
Bibliographic record
Abstract
Screening for eating disorders (EDs) in adolescent females with type 1 diabetes (T1D) is recommended by national guidelines because of the increased risk of EDs in this population and the premature morbidity and mortality associated with this dual diagnosis (1). Currently, no ED screening tool has been validated and accepted for clinical use in T1D. We modified the SCOFF ED screening questionnaire for this population (mSCOFF) and compared it with the Eating Disorder Inventory-3 (EDI-3) in 43 adolescent females with T1D (mean ± SD age 15.8 ± 1.7 years, diabetes duration 7.6 ± 3.9 years, BMI 25.5 ± 3.5 kg/m2, A1C 8.4 ± 1.4% [68 mmol/mol]). Patients with known ED were excluded. This study had institutional ethics board approval. The EDI-3 is a reliable, valid, 91-item self-report measure for screening ED risk (2). A modified form of the EDI (mEDI) eliminates questions related to diabetes-imposed dietary …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".