Response to Letter to the Editor From Rosenfield et al: “Recommendations From the 2023 International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome”
Bibliographic record
Abstract
Journal Article Accepted manuscript Response to Letter to the Editor from Rosenfield, et al: Recommendations from the 2023 International Evidence-based Guideline for the Assessment and Management of Polycystic Ovary Syndrome Get access Helena Teede, Helena Teede Monash Centre of Health Research and Implementation, Monash University, Melbourne Australia Corresponding author: Helena Teede - Helena.teede@monash.edu. https://orcid.org/0000-0001-7609-577X Search for other works by this author on: Oxford Academic Google Scholar Chau Tay, Chau Tay Monash Centre of Health Research and Implementation, Monash University, Melbourne Australia Search for other works by this author on: Oxford Academic Google Scholar Ricardo Azziz Ricardo Azziz University of Alabama, Women and Infants Center, Birmingham, Alabama, USA Search for other works by this author on: Oxford Academic Google Scholar The Journal of Clinical Endocrinology & Metabolism, dgae370, https://doi.org/10.1210/clinem/dgae370 Published: 29 May 2024 Article history Received: 03 May 2024 Revision received: 21 May 2024 Editorial decision: 24 May 2024 Accepted: 28 May 2024 Published: 29 May 2024
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".