Digit ratios do not serve as anatomical evidence of prenatal androgen exposure in clinical phenotypes of polycystic ovary syndrome
Bibliographic record
Abstract
BACKGROUND: Polycystic ovary syndrome (PCOS) is heterogeneous in its clinical presentation and four major phenotypes have been identified. The precise etiology of PCOS is unknown; however, variable exposure to prenatal androgens may be responsible for the spectrum of endocrine and metabolic disturbances characteristic of this syndrome. Since prenatal testosterone exposure is known to decrease the ratio of the second to fourth finger lengths (2D:4D), we characterized the left and right hand 2D:4D in women with clinical variants of PCOS. We hypothesized that if prenatal androgens were involved in the development of the phenotypic spectrum of PCOS, then lower 2D:4D would be differentially expressed among clinical variants of the syndrome. METHODS: Digit ratios were determined in 98 women diagnosed with PCOS by the 2003 international consensus guidelines and in 51 women with regular menstrual cycles, no clinical or biochemical signs of hyperandrogenism and normal ovarian morphology. Women with PCOS were categorized into four clinical phenotypes (i.e. Frank, Non-PCO, Ovulatory and Mild) and 2D:4D among groups were compared by Tukey-Kramer multiple comparisons tests. RESULTS: Left (P = 0.77) and right (P = 0.68) hand 2D:4D were similar among the four clinical phenotypes and no phenotype of PCOS demonstrated a 2D:4D that differed from controls (Left Hand, P = 0.44 and Right Hand, P = 0.75). CONCLUSIONS: Women with PCOS do not demonstrate finger length patterns that are consistent with increased prenatal androgen exposure. These findings do not preclude a role for prenatal androgens in the development of PCOS; however, low 2D:4D are not a characteristic of PCOS.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".