A Comparison of CAROC and FRAX in Patients with Fragility Fracture
Bibliographic record
Abstract
Osteoporosis and the resultant clinically relevant outcome, fractures, are ever increasing in our aging population. Fractures are associated with increased pain, disability, and loss of quality of life, characteristics comparable to those seen in similar chronic diseases such as arthritis and lung disease; not to mention the cost to the patient and society in general1,2. Fractures are also associated with frailty, and both frailty and fractures are often predictive of future fractures3. Hip and vertebral fractures are associated with increased morbidity and mortality4, yet when it comes to those at the highest risk of fracturing5,6, we often fail to intervene, and the care gap7 that we have seen in the past remains today6. It is not uncommon to see patients with multiple fractures continue to fracture without any apparent recognition that these might be caused by osteoporosis6 — even … Address correspondence to Dr. J.D. Adachi, 501-25 Charlton Ave. E., Hamilton, Ontario L8N 1Y2, Canada; E-mail: jd.adachi{at}sympatico.ca
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".