Test-Retest Reliability and External Validity of Canadian Diabetes Risk Questionnaire - Turkish
Bibliographic record
Abstract
Objectives: The aim of the study was to examine the test-retest reliability and external validity of the Canadian Diabetes Risk Questionnaire (CanRisk). Materials and Methods: Individuals over 40 years of age without any disease were included in the study. Participants were administered the CanRisk, Nottingham Health Profile (NHP), and Visual Analog Scale (VAS). CanRisk test-retest validity was calculated with the interclass correlation coefficient (ICC), and external validity was calculated with the Pearson correlation coefficient. Results: The study included 1349 participants, 549 men and 755 women (mean age 50.03 ± 8.05 years). CanRisk test-retest validity was found to be excellent (0.99). Its external validity was evaluated by examining its correlation with NHP, and it was found that there was a statistically significant, positive weak correlation (p<0.05, r= 0.23). Conclusion: CanRisk -TR was found to be a reliable and valid questionnaire to predict diabetes risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".