A longitudinal examination of perinatal testosterone, estradiol and vitamin D as predictors of handedness outcomes in childhood and adolescence
Bibliographic record
Abstract
could play an important role. Prenatal testosterone and Vitamin D exposure are considered, yet findings and interpretations remain equivocal. We examined n = 767 offspring from a population-based pregnancy cohort (The Raine Study) for whom early biological data and childhood/adolescent handedness data were available. We tested whether 18-week maternal circulatory Vitamin D (25[OH]D), and testosterone and estradiol from umbilical cord blood sampled at birth predicted variance in direction of hand preference (right/left), along with right- and left-hand speed, and the strength and direction of relative hand skill as measured by a finger-tapping task completed at 10 (Y10) and/or 16 (Y16) years. Although higher concentrations of Vitamin D predicted more leftward and less lateralized (regardless of direction) relative hand skill profiles, taken as a whole, statistically significant findings typically did not replicate across time-point (Y10/Y16) or sex (male/female) and were rarely detected across different (bivariate/multivariate) levels of analysis. Considering the number of statistical tests and generally inconsistent findings, our results suggest that perinatal testosterone and estradiol contribute minimally, if at all, to subsequent variance in handedness. Vitamin D, however, may be of interest in future studies.
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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 | 0.002 |
| 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) | 0.001 | 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 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".