Review of global epidemiology data for alopecia areata highlights gaps and a call for action
Bibliographic record
Abstract
Journal Article Corrected proof Review of global epidemiology data for alopecia areata highlights gaps and a call for action Get access Cathryn Sibbald, Cathryn Sibbald Writing - original draft, Writing - review & editing Division of Dermatology, Department of Paediatrics, SickKids Hospital, Toronto, ON, CanadaDivision of Dermatology, Department of Medicine, University of Toronto, Toronto, ON, Canada Correspondence: Cathryn Sibbald. Email: cathryn.sibbald@sickkids.ca https://orcid.org/0000-0001-9288-1121 Search for other works by this author on: Oxford Academic Google Scholar Leslie Castelo-Soccio Leslie Castelo-Soccio Writing - review & editing National Institute of Arthritis and Musculoskeletal and Skin Diseases, Bethesda, MD, USA https://orcid.org/0000-0003-3289-446X Search for other works by this author on: Oxford Academic Google Scholar British Journal of Dermatology, ljae088, https://doi.org/10.1093/bjd/ljae088 Published: 01 March 2024 Article history Received: 21 February 2024 Accepted: 23 February 2024 Published: 01 March 2024 Corrected and typeset: 15 March 2024
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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".