REACTION TIMES ON THE ATTENTION NETWORK TEST ARE ASSOCIATED WITH TRAFFIC VIOLATIONS
Bibliographic record
Abstract
The Attention Network Test (ANT) measures choice response time (RT) and the efficiency of three functions of attention (alerting, orienting, and executive function). Using data from the Candrive cohort study, we looked for associations between overall median RT from the ANT and traffic violations. Participants (N = 451) were aged ≥70. Violations data were obtained from provincial ministries of transportation and dichotomized as the primary outcome measure (yes/no). Our logistic regression included ANT median RT, gender, number of self-reported medical conditions, and self-reported kilometers driven (low = 1–10,000km/year, high = >10,000km/year) as explanatory variables. In the adjusted model, drivers with higher RT had greater odds of traffic violations (OR=1.32, p < .001) as did participants who drove greater distances (OR=2.67, p < .001). Gender and the number of medical conditions were not associated with violations. These results suggest the ANT may provide insight into cognitive processes supporting safe driving.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".