Profile of 24-h Light Exposure and Circadian Phase of Melatonin Secretion in Night Workers
Bibliographic record
Abstract
Light exposure was measured in 30 permanent night nurses to determine if specific light/dark profiles could be associated with a better circadian adaptation. Circadian adaptation was defined as a significant shift in the timing of the episode of melatonin secretion into the daytime. Light exposure was continuously recorded with ambulatory wrist monitors for 56 h, including 3 consecutive nights of work. Participants were then admitted to the laboratory for 24 h where urine was collected every 2 h under dim light for the determination of 6-sulphatoxymelatonin concentration. Cosinor analysis was used to estimate the phase position of the episode of melatonin secretion. Five participants showed a circadian adaptation by phase delay ("delayed participants") and 3 participants showed a circadian adaptation by phase advance ("advanced participants"). The other 22 participants had a timing of melatonin secretion typical of day-oriented people ("nonshifters"). There was no significant difference between the 3 groups for total light exposure or for bright light exposure in the morning when traveling home. However, the 24-h profiles of light exposure were very distinctive. The timing of the main sleep episode was associated with the timing of light exposure. Delayed participants, however, slept in darker bedrooms, and this had a major impact on their profile of light/dark exposure. Delayed and advanced participants scored as evening and morning types, respectively, on a morningness-eveningness scale. This observation suggests that circadian phase prior to night work may contribute to the initial step toward circadian adaptation, later reinforced by specific patterns of light exposure.
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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 | 0.001 |
| 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 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".