Sex- and Site-Specific Reference Data for Bone Microarchitecture in Adults Measured Using Second-Generation HR-pQCT
Bibliographic record
Abstract
There are currently no population-based reference data sets available for volumetric bone mineral density and microarchitecture parameters measured using the second-generation high-resolution peripheral quantitative computed tomography (HR-pQCT), yet the technology is rapidly becoming a standard for studies of bone microarchitecture. Although cross-calibrated data sets from the first-generation HR-pQCT have been reported, they are not suitable for second-generation bone microarchitecture properties because of fundamental differences between scanner generations. This study provides site- and sex-specific centile curves across the adult life span for second-generation HR-pQCT properties. A total of 1236 adult participants (768 female and 468 male) from the Calgary area between the ages of 18 and 90 years were scanned at the distal tibia and radius using the second-generation HR-pQCT. Bone densities, microarchitectural properties, and failure load estimated using finite element analysis were determined using standard in vivo protocol. Site- and sex-specific centile curves were generated using the generalized additive models for location, scale, and shape (GAMLSS) method. These data provide reference curves appropriate for predominantly white male and female adults, which can be used as a tool to assess patient- or cohort-specific bone health. © 2020 American Society for Bone and Mineral Research.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".