Bibliographic record
Abstract
Asymmetry of the human axial skeleton has received much less attention that of the limb skeleton. Pelvic morphology is subject to multiple selective factors, including bipedal locomotion and obstetrics, among others, as well as environmental factors such as biomechanical loading. How these various factors influence or restrict asymmetry of the pelvis is unknown and few studies have investigated levels and patterns of pelvic asymmetry. This study examines percentage directional (%DA) and absolute (%AA) asymmetry in 14 bilaterally paired dimensions of the pelvic canal, non-canal pelvis, and femur in female (n = 111) and male (n = 126) skeletons from nine geographically dispersed skeletal samples. Directional asymmetries were uniformly low for all measures and lacked any consistent patterning across the variables, while %AA was highest in the pelvic canal, particularly the posterior aspects. Few sex differences and no population differences were found for %DA and %AA; however the latter was correlated with coefficients of variation across the 14 variables in both sexes. While sample mean %DA were low, standard deviations of the canal variables were high and the majority of individuals in both sexes displayed %DA values >±0.5, suggesting asymmetry is common, if not directionally consistent. Biomechanical loading of the pelvic girdle may influence asymmetry of both the canal and non-canal aspects of the pelvis; however it is unlikely that these asymmetries negatively affect obstetric function, given the prevalence for %DA found in this study. Anat Rec, 300:653-665, 2017. © 2017 Wiley Periodicals, Inc.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".