Fatigue Risk of Long-Distance Driver as the Impact of the Duration of Work
Bibliographic record
Abstract
Studies on the driver's fatigue, must focus on at least two things: the time-of-day that affect by circadian factors, and time-on-task. This paper discusses the risk level of driver fatigue, which generally have to drive in a long duration or more than 4 hours. The risk of fatigue was assessed using Fatigue Likelihood Scoring (FLS) by Transport Canada. Based on interviews with 24 inter-city bus drivers, 18 of the 24 drivers have a very high risk of fatigue that characterized by FLS scores greater than 20, while the rest have a high risk driver that characterized by FLS value greater than 10. A high risk of chronic fatigue that experienced by most of drivers caused by working hours which is more than 36 hours in a week, the duration of the shift of greater than 8 hours a day, lack of time off, the amount hours of driving at night, and the amount of time off.
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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 | 0.000 | 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) | 0.000 | 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".