Three Navigation Systems With Three Tasks: Using the Lane-Change Test (LCT) to Assess Distraction Demand
Why this work is in the frame
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Bibliographic record
Abstract
The Lane Change Test (ISO, 2008; Mattes, 2003) was used to assess distraction demand when drivers completed three typical navigation tasks (an easy navigation task, a point of interest task and a difficult navigation task) using three different navigation systems. In order for the LCT to be a useful procedure, it must distinguish good from poor navigation systems and acceptable from unacceptable tasks performed using those systems. The results provide some general support for the LCT as a sensitive measure of distraction. Some aspects of the results, however, called into question the adequacy of the LCT as a sufficient measure of distraction. In particular, the LCT was found to be insensitive to task demands arising from excessive task duration. Since risk exposure is a function of secondary task duration (as well as other factors such as intensity, frequency and timing), it is recommended that a measure of task duration be incorporated in the LCT procedure. When the MDEV was modified to incorporate task duration, the resulting measure (mean deviation per average task) reflected more adequately the interaction demands of the various navigation tasks.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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