Near Peripheral Motion Detection Threshold Predicts Detection Failure Accident Risk in Younger and Older Drivers
Bibliographic record
Abstract
Motion contrast thresholds for 0.4 cycle/degree drifting Gabor stimuli were assessed at 15-degrees eccentricity for 16 younger drivers (ages 24 to 42), and 15 older drivers (ages 65 to 84), using a temporal two-alternative forced choice staircase procedure. Two self-report questionnaires assessed detection failure accident risk—the Driver Perception Questionnaire (DPQ5), and an abridged Aging Driver Questionnaire (ADQ15). The UFOV® test battery was also administered. Mean peripheral motion contrast thresholds (PMCT) of younger and older participants were –39.3 dB and –33.8 dB, respectively. For younger drivers, the correlation between PMCT and DPQ5 scores was .62 (p<.01), and between DPQ5 and ADQ16 (new and validated self-report measures, respectively) was .59 (p<.01). For older drivers, correlation between PMCT and DPQ5 scores was .49 (p<.01), between DPQ5 and ADQ16 was .73 (p<.01), and between PMCT and age was .49 (p<.05). For drivers overall, correlation was .48 (p<.01) between PMCT and DPQ5 scores, .63 (p<.0001) between DPQ5 and ADQ16, and .69 (p<.0001) between PMCT and age. For drivers overall, correlation was .30 (p<.05) between UFOV1 and age, .67 (p<.0001) between UFOV2 and age, .56 (p<.001) between UFOV2 and PMCT, .80 (p<.0001) between UFOV3 and age, and .58 (p<.001) between UFOV3 and PMCT. Holding age constant, partial correlation of PMCT with DPQ5 was .55 (p<.001), and of PMCT with ADQ15 was .39 (p<.05). PMCT significantly predicted self-reported driving performance in a laboratory setting, and worsened significantly with age. PMCT assessment should be made practicable. Informing high-risk drivers may encourage appropriate risk reduction countermeasures.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 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".