0691 A FIELD STUDY OF MARINE PILOTS’ PERFORMANCE, FATIGUE, AND SLEEPINESS LEVELS
Bibliographic record
Abstract
Working on atypical schedules leads to sleep-wake disturbances and increased fatigue. This study aims to quantify how time-of-day, work duration, and time awake interact to affect ship pilots’ performance and sleepiness. A total of 17 male St-Lawrence River ship pilots (46.0 ± 7.2 years; ±SD) participated to a 16–21 day field study comprised of a succession of work and rest days. The sleep-wake cycle was documented by wrist-worn actigraphy and sleep-wake log. Performance was assessed by a 5-min psychomotor vigilance task (PVT) at the start and end of each work and rest day. Sleepiness and fatigue were assessed 5x/day by the Karolinska sleepiness scale (KSS) and the Samn Perelli Fatigue scale, respectively. Probability of presenting increased sleepiness and fatigue as well as reduced performance was modelled using repeated measure logistic regressions. Specifically, the probability of exceeding 1 SD from each individual’s mean was modelled. Ship transits occurred throughout the 24-hour day and lasted in average (±SEM) 5:56 ± 0:22h. The probability of reduced reaction speed, elevated fatigue, and sleepiness levels significantly varied as a function of time-of-day (p≤0.002) and increased with work duration (p≤0.029). These factors interacted such that the effect of work duration on all dependent variables was more prononced when the transit ended at the end of the night. The effect of time-of-day was less and more prononced with shorter and longer transit durations, respectively. A similar interaction was observed for the duration of waking (p>0.001) and time-of-day (p≤0.029) on probability of elevated fatigue and sleepiness. Ship pilots’ performance, fatigue, and sleepiness levels are sensitive to work duration, time awake, and time-of-day. In this group, the worst scores occurred when longer transits ended at the end of the night. This study was supported by the Laurentian Pilotage Authority and the Corporation des Pilotes du Saint-Laurent Central
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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) | 0.001 | 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 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".