Controversies Surrounding the BMD Reporting Standard for the Determination of 10-Year Absolute Fracture Risk: A Canadian Perspective
Bibliographic record
Abstract
The Canadian Association of Radiologists and Osteoporosis Canada currently endorse a fracture risk prediction tool called CAROC. It has been used in Canada since 2005 with an update in 2010. It is an integral part of bone mineral densitometry reporting across the country. New osteoporosis guidelines from Osteoporosis Canada (OC) are expected in the near future. There has been pressure on radiologists to report fracture risk using an alternative fracture risk prediction platform called FRAX. In addition, OC collaborated in the development of the Canadian FRAX model and has been copromoting both FRAX and CAROC, raising the prospect that new guidelines may seek to replace CAROC with FRAX for fracture risk determination. A number of concerns have been raised about FRAX, including: (1) FRAX has not released its algorithms to the public domain with the consequence that it is impossible to verify results for an individual patient; (2) FRAX has incorrectly claimed that it was developed by the World Health Organization (WHO) and has used this affiliation to promote itself until recently ordered by the WHO to desist; (3) FRAX requires collection of additional clinical information beyond that needed for CAROC, and this patient-reported medical data is prone to substantial error; and (4) despite claims to the contrary, there are no valid studies comparing FRAX to CAROC. We believe it is important that radiologists be aware of these issues in order to provide input into future Technical Standards for Bone Mineral Densitometry Reporting of the Canadian Association of Radiologists.
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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 | 0.156 | 0.299 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.020 | 0.007 |
| Research integrity | 0.018 | 0.035 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".