Tibial cortical and trabecular variables together can pinpoint the timing of impact loading relative to menarche in premenopausal females
Bibliographic record
Abstract
OBJECTIVES: Though relationships between limb bone structure and mechanical loading have provided fantastic opportunities for understanding the lives of prehistoric adults, the lives of children remain poorly understood. Our aim was to determine whether or not adult tibial skeletal variables retain information about childhood/adolescent loading, through assessing relationships between cortical and trabecular bone variables and the timing of impact loading relative to menarche in premenopausal adult females. METHODS: Peripheral quantitative computed tomography was used to quantify geometric and densitometric variables from the proximal tibial diaphysis (66% location) and distal epiphysis (4% location) among 81 nulliparous young adult female controls and athletes aged 19-33 years grouped according to intensity of impact loading both pre- and post-menarche: (1) Low:Low (Controls); (2) High:Low; (3) High:High; (4) Moderate:Moderate; (5) Low:Moderate. ANCOVA was used to compare properties among the groups adjusted for age, stature, and body mass. RESULTS: Significant increases in diaphyseal total cross-sectional area and strength-strain index were documented among groups with any pre-menarcheal impact loading relative to groups with none, regardless of post-menarcheal loading history (p < .01). In contrast, significantly elevated distal trabecular volumetric bone mineral density was only documented among groups with recent post-menarcheal loading relative to groups with none, regardless of pre-menarcheal impact loading history (p < .01). CONCLUSIONS: The consideration of diaphyseal cortical bone geometric and epiphyseal trabecular bone densitometric variables together within the tibia can identify variation in pre-menarcheal and post-menarcheal impact loading histories among premenopausal adult females.
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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 | 0.001 | 0.000 |
| 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".