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 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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".