DOES SAMPLE ATTRITION DECREASE THE GENERALIZABILITY OF THE FINDINGS IN THE CANDRIVE II COHORT STUDY?
Bibliographic record
Abstract
The Candrive II cohort researchers have followed a convenient sample of older drivers, aged 70 and older, for five to seven years. One of the goals of this study consists in developing a risk stratification tool that would help identify unsafe older drivers. The validity of such tools depends on how representative the study sample is. We have demonstrated that the Candrive II sample at baseline was representative of older Canadian driver through demonstration of equivalence on variables extracted from the Canadian Community Health Survey – Healthy Aging (CCHS-HA). At baseline, 928 older drivers (mean age = 76.21 5) volunteered in the Candrive II study with 583 of them remaining 5 years later (mean age = 79.8,). We make again use of the equivalence testing approach to compare Candrive II sample at year 5 to CCHS-HA drivers of the same age.
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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 | 0.431 | 0.598 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".