Circadian Countermeasures in the High Arctic during Summer
Bibliographic record
Abstract
Abstract : Background. We have previously shown that the 24 hours of daily sunlight in the high Arctic during the summer provides a good environment for misaligning the physiological circadian pattern with the work-sleep schedule of the individual. As a result, there is a prevalence of sleep difficulty in the summer, with a general reduction in both the quantity and quality of sleep obtained among residents in the summer vs. the winter (Paul, M. A., Love, R. J., Hawton, A. M.et al. Melatonin production, sleep patterns and modeled performance effectiveness in subjects in the high Arctic. In. DRDC-RDDC-2014-R15, DRDC Toronto Research Centre, 2014).Methods. Subjects were 15 CAF personnel (11 males and 4 females, age range of 19 to 47 years, with mean age and standard deviation of 28.3 8.3 years) who had arrived at CFS Alert at least one week prior to the study which encompassed 21 days from May 23rd to June 13th, 2014. During this period there were 24 hours of daylight. Subjects wore motion-detection devices (Actigraphs) to obtain objective sleep data, and completed questionnaires regarding sleep difficulty and psychosocial parameters at the beginning and end of the study. After a 7 day period of baseline Actigraph data, salivary melatonin assays were collected 2 hourly for 24 hours while the subjects remained in dim light conditions. Based on the melatonin profiles and sleep questionnaire histories, 13 subjects were prescribed melatonin and given advice about light exposure. After a 10 day intervention period, a 24hour melatonin profile was repeated under identical conditions. Treatment effects were evaluated using the questionnaire data, actigraphic data, and endogenous melatonin profiles. Results. A small benefit of exogenous melatonin consumption was observed in 73 of the subjects. However, there was no statistically significant difference in the collective quantity or quality of sleep obtained by the subjects following the treatment.
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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 | 0.000 | 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 | 0.001 | 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 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".