Is sexual dimorphism in morphometric variables of the proximal femur moderated by age in adulthood? A cross-sectional study in Ghana
Bibliographic record
Abstract
Ageing may impact proximal femoral morphometry in both males and females. However, it is not clear whether the observed sexual dimorphism is attributable to an ageing effect in the post-pubertal period. The potential effect of ageing on sexual dimorphism in the proximal femur is most significantly relevant for forensic and osteoarchaeological research. The study was cross-sectional and comprised 123 participants (females = 72 and males = 51), who were recorded between January 2017 and June 2018 at the Korle-Bu Teaching Hospital. The study participants were aged between 31 and 79 years. The femoral head diameter, the femoral neck diameter, the femoral neck-shaft angle, and the femoral hip axis length were measured from the right side by radiographic technique and following standard osteometry methods. The femoral head-neck ratio was then calculated. All measurements were taken twice and then averaged. The (mean ± SD) femoral head diameter was higher in males (5.1 ± 0.56 cm) than in females (4.8 ± 0.51 cm) with a moderate effect size (p = 0.023, Hedge’s g = 0.56). Similarly, the femoral neck diameter was higher in males (4.0 ± 0.52 cm) than in females (3.8 ± 0.48 cm) with a small effect size (p = 0.025, Hedge’s g = 0.40). The femoral head axis length increased by 0.03 cm annually in males. The observed sexual dimorphism in the femoral head and neck diameters could not, however, be attributable to the ageing effect. Ageing may not have an impact on sexual dimorphism in the femoral head and neck diameters among persons older than 30 years in the Ghanaian population.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".