Skeletal variability in the pelvis and limb skeleton of humans: Does stabilizing selection limit female pelvic variation?
Bibliographic record
Abstract
OBJECTIVES: This study tests the hypothesis, a correlate of the obstetric dilemma, that skeletal variability in the human female pelvic canal is limited owing to the action of stabilizing selection. Levels of variation in three skeletal regions (pelvic canal, noncanal pelvis, and limbs) of females and males are compared to each other and between sexes. METHODS: Nine human skeletal samples (total female n = 101; male n = 117) representing diverse populations were included. Osteometric data were collected from the articulated pelvis, os coxa, sacrum, femur, tibia, humerus, radius, and clavicle. Coefficients of variation, adjusted for small sample size (V*), were calculated for variables in separate samples by sex, and mean V*s were taken for the skeletal regions. Size variances were measured as V* of the geometric mean (GM) of the skeletal region variables. Using nonparametric methods, coefficients were compared between sexes and skeletal regions and correlations among V*s were calculated. RESULTS: Females and males do not differ in levels of variation for any skeletal region. The pelvic canal is the most variable region in both sexes, while size variability (GM) is similar among the three skeletal regions. Across the samples, canal and noncanal pelvic regions share patterns of variability in females but not males, while variability of the limb skeleton is independent in both sexes. CONCLUSIONS: The results suggest that stabilizing selection does not limit variability in the female pelvic canal. Biological plasticity may be greater in the canal than that in other skeletal regions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".