Visual Attention Cut Points for Driver Fitness in Parkinson’s Disease
Bibliographic record
Abstract
This study determined whether the Useful Field of View™ Risk Index (UFOV RI) adds value as a predictor of on-road outcomes in drivers with Parkinson’s disease (PD) when considered with age, gender, and disease severity and compared with community-dwelling older drivers (Controls). A total of 101 PD drivers and 138 Controls underwent a comprehensive driving evaluation, including an on-road assessment. Logistic regression analyses determined the associations of age, gender, visual attention, and disease severity to on-road outcomes. Receiver operating characteristic curve analyses determined the optimal UFOV RI cut points to predict on-road outcomes. Above adding age and gender, the UFOV RI alone predicted on-road outcomes in PD, while the UFOV RI and age predicted on-road outcomes in Controls. Regardless of disease severity, visual attention was more impaired in PD than in Controls. The UFOV RI cut point of 3 provided the fewest misclassifications ( n = 25) in PD. The UFOV RI is a valid screening predictor of on-road outcomes across PD drivers of different disease severity, but has moderate sensitivity and specificity.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".