Concurrent Validity of a Virtual Reality Driving Assessment for Persons with Brain Injury
Why this work is in the frame
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Bibliographic record
Abstract
In this article, we present the results of a pilot study to examine the driving performance of persons with brain injury using virtual reality (VR) technology. A total of 28 adult persons with a brain injury (22 males, 6 females) participated in a standardized driving evaluation, which included a VR driving environment, known as the DriVR. Concurrent validity of the DriVR was examined by comparing DriVR measures to other indicators of driving ability, which consisted of on-road, cognitive and visual-perceptual, and driving video tests. Statistically significant DriVR inter-correlations using the Bonferroni correction were found between following a pace car (Follow Traffic Event), and correctly parking a car (Driveway Choice Event) (r pb = - .65, p< .003), as well as for two measures of lane tracking (Shop Road and Opposite Road), (r = .98, p< .003). The DriVR appeared to be a useful adjunctive screening tool for assessing driving performance in persons with brain injury. However, as with any new assessment and intervention tool, it will need to undergo further empirical validation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it