Using Video Replay of Simulated Driving to Estimate Driving Safety and Cognitive Status
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cognitive decline resulting from Dementia of Alzheimer’s Type (DAT) can lead to reduced ability to perform complex daily tasks required for independent living, including driving an automobile. This study explores the ability of untrained observers to classify driving safety using short video clips of simulated driving through intersections; it also examined whether untrained observers could predict whether the driver was cognitively healthy or cognitively impaired. Participants (n = 54) were shown a series of 30 video clips arranged in an online survey and asked to answer questions following each clip regarding the safety of the maneuver and the cognitive status of the driver. Results showed that participants’ subjectively rated DAT drivers as significantly less safe in comparison to control drivers, F (1, 52) = 228.44, p < 0.001. Participant’s classification of DAT drivers and controls was also significantly higher than chance (i.e., >50% correct). Findings provide preliminary support for the development of a clinical decision-making aid using video replay of driving simulator performance in fitness-to-drive assessments for individuals with cognitive impairment.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it