Impaired Performance in Commercial Drivers
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
Sleepiness plays an important role in major crashes of commercial vehicles. Because determinants are likely to include inadequate sleep and sleep apnea, we evaluated the role of short sleep durations over 1 wk at home and sleep apnea in subjective sleepiness (Epworth Sleepiness Scale), objective sleepiness (reduced sleep latency as determined by the Multiple Sleep Latency Test), and neurobehavioral functioning (lapses in performance, tracking error in Divided Attention Driving Task) in commercial drivers. Studies were conducted in 247 of 551 drivers at higher risk for apnea and in 159 of 778 drivers at lower risk. A multivariate linear association between the sets of outcomes and risk factors was confirmed (p < 0.0001). Increases in subjective sleepiness were associated with shorter sleep durations but not with increases in severity of apnea. Increases in objective sleepiness and performance lapses, as well as poorer lane tracking, were associated with shorter sleep durations. Associations with sleep apnea severity were not as robust and not strictly monotonic. A significant linear association with sleep apnea was demonstrated only for reduced sleep latency. The effects of severe apnea (apnea-hypopnea index, at least 30 episodes/h), which occurred in 4.7%, and of sleep duration less than 5 h/night, which occurred in 13.5%, were similar in terms of their impact on objective sleepiness. Thus, addressing impairment in commercial drivers requires addressing both insufficient sleep and sleep apnea, the former being more common.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it