Digit ratios by computer-assisted analysis confirm lack of anatomical evidence of prenatal androgen exposure in clinical phenotypes of polycystic ovary syndrome
Bibliographic record
Abstract
BACKGROUND: We recently showed that women with four clinical phenotypes of polycystic ovary syndrome (PCOS) do not demonstrate anatomical evidence of elevated prenatal androgen exposure as judged by a lower ratio of the index (2D) to ring (4D) finger. However, those findings conflicted with a previous study where women with PCOS had lower right hand 2D:4D compared to healthy female controls. Both these studies used Vernier calipers to measure finger lengths--a method recently shown to be less reliable at obtaining finger length measurements than computer-assisted analysis. METHODS: Ninety-six women diagnosed with PCOS according to the 2003 Rotterdam criteria had their finger lengths measured with computer-assisted analysis. Participants were categorized into four recognized phenotypes of PCOS and their 2D:4D compared to healthy female controls (n = 48) and men (n = 50). RESULTS: Digit ratios assessed by computer-assisted analysis in women with PCOS did not differ from female controls, but were significantly lower in men. When subjects were stratified by PCOS phenotype, 2D:4D did not differ among phenotypes or when compared to female controls. CONCLUSION: Computer-assisted measurements validated that digit ratios of women with PCOS do not show anatomical evidence of increased prenatal androgen exposure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".