A study of the indicators that are associated with selfreported fatigue by officers of the watch
Bibliographic record
Abstract
Limited research exist examining fatigue and its indicators among seafarers. The \npurpose of this exploratory research was to determine the influence of occupational, \nindividual, and environmental factors on subjective fatigue among officers of the watch. \nData was collected from 21 participants dispatched on vessels in the Canadian offshore \nsector. Self-reported questionnaire methods (pre-voyage, before watch, and after watch) \nwere employed to collect data on momentary subjective physical and mental fatigue for \ncomparison with occupational, individual, and environmental factors while on a seagoing \ntrip. Mixed multi-level linear model analysis revealed differences across individuals and \nthe factors that influence before watch and after watch perceptions of fatigue. These \nfactors include caffeine consumption, sleep quality perceptions, environmental factors \nsuch as noise and motion, and psychosocial work factors. Age was also found to be an \ninteraction factor with some of these variables. Further future research needs to be \nconducted to explore this analysis tool among more maritime employees.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".