Combinations of trabecular and cortical bone properties distinguish various loading modalities between athletes and controls
Bibliographic record
Abstract
OBJECTIVES: Variation in trabecular and cortical bone properties is often used to infer habitual behavior in the past. However, the structures of both types of bone are rarely considered together and may even contradict each other in functional interpretations. We examine trabecular and cortical bone properties in various athletes and sedentary controls to clarify the associations between combinations of cortical and trabecular bone properties and various loading modalities. MATERIALS AND METHODS: We compare trabecular and cortical bone properties using peripheral quantitative computed tomography scans of the tibia between groups of 83 male athletes (running, hockey, swimming, cricket) and sedentary controls using Bayesian multilevel models. We quantify midshaft cortical bone rigidity and area (J, CA), midshaft shape index (Imax/Imin), and mean trabecular bone mineral density (BMD) in the distal tibia. RESULTS: All groups show unique combinations of biomechanical properties. Cortical bone rigidity is high in sports that involve impact loading (cricket, running, hockey) and low in nonimpact loaded swimmers and controls. Runners have more anteroposteriorly elliptical midshafts compared to other groups. Interestingly, all athletes have greater trabecular BMD compared to controls, but do not differ credibly among each other. DISCUSSION: Results suggest that cortical midshaft hypertrophy is associated with impact loading while trabecular BMD is positively associated with both impact and nonimpact loading. Midshaft shape is associated with directionality of loading. Individuals from the different categories overlap substantially, but group means differ credibly, suggesting that nuanced group-level inferences of habitual behavior are possible when combinations of trabecular and cortical bone are analyzed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".