Asymmetry in linear measurements and cross‐sectional geometry in the humerus during ontogeny
Bibliographic record
Abstract
Abstract Objectives Adult upper limb asymmetry is used to reconstruct behavior. However, the developmental trajectory of asymmetry in bone length, cross‐sectional geometry (CSG), and joint dimensions is poorly understood. This study examines the development trajectory of humeral asymmetry and if asymmetry in bone length, joint size, and CSG develop in concert. Materials and Methods Linear measurements of bone length and metaphyseal/epiphyseal breadth, bending rigidity (Imax and Imin), and cross‐sectional shape (Imax/Imin) at 30%, 50%, and 70% of bone length were acquired from 3D models of humeri from four skeletal samples of prehistoric hunter‐gatherer populations (n = 82). Dental age cohorts were used to assess ontogenetic trends. Percent absolute (%AA) and directional (%DA) asymmetry were calculated for paired measures. Percentage of matching direction of asymmetry across variables and correlation analysis tested relationships between variables. Results Within the total pooled sample, Imax shows the highest %AA and %DA, followed by shape and linear dimensions. Asymmetry is lowest in neonates and increases with age, particularly %DA of Imax in mid‐proximal sections. Correlations among variables are low to moderate and strongest between Imax measures. Matching direction of asymmetry between variables is low and generally increases with age. Discussion Higher correlations with age in CSG likely indicate greater responsiveness to mechanical loading. Low correlations in magnitude of asymmetry and side dominance suggest independence in the development of asymmetry between maximum rigidity, shape, and linear measures. Differences in how asymmetric loading affects the ontogeny of linear and CSG variables may account for the heterogeneous development of asymmetry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".