Sex‐specific patterns in cortical and trabecular bone microstructure in the Kirsten Skeletal Collection, South Africa
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to provide bone histomorphometric reference data for South Africans of the Western Cape who likely dealt with health issues under the apartheid regime. METHODS: male = 131, mean = 47.9 ± 15.8 years) from the Kirsten Skeletal Collection, U. Stellenbosch, lived in the Cape Town metropole from the late 1960s to the mid-1990s. To study age-related changes in cortical and trabecular bone microstructure, photomontages of mid-thoracic rib cross-sections were quantitatively examined. Variables include relative cortical area (Rt.Ct.Ar), osteon population density (OPD), osteon area (On.Ar), bone volume fraction (BV/TV), trabecular number (Tb.N), trabecular thickness (Tb.Th), and trabecular spacing (Tb.Sp). RESULTS: All cortical variables demonstrated significant relationships with age in both sexes, with women showing stronger overall age associations. Peak bone mass was compromised in some men, possibly reflecting poor nutritional quality and/or substance abuse issues throughout adolescence and early adulthood. In women, greater predicted decrements in On.Ar and Rt.Ct.Ar suggest a structural disadvantage with age, consistent with postmenopausal bone loss. Age-related patterns in trabecular bone microarchitecture are variable and difficult to explain. Except for Tb.Th, there are no statistically significant relationships with age in women. Men demonstrate significant negative correlations between BV/TV, Tb.N, and age, and a significant positive correlation between Tb.Sp and age. CONCLUSIONS: This research highlights sex-specific differences in patterns of age-related bone loss, and provides context for discussion of contemporary South African bone health. While the study sample demonstrates indicators of poor bone quality, osteoporosis research continues to be under-prioritized in South Africa.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".