A Blue-Enriched Light Intervention Counteracts the Alertness Decrement Among Mine Workers on Extended 12-Hour Night Shift Periods
Bibliographic record
Abstract
OBJECTIVE: The aim of the study is to assess whether a blue-enriched light intervention improves nocturnal alertness and daytime sleep of night workers. METHODS: Thirteen miners performing 12-hour night shifts for 12 consecutive nights were exposed to a baseline and a blue-enriched light condition. All subjects wore an actigraph and completed a Psychomotor Vigilance Task at the beginning and at the end of each shift. Data were analyzed with linear mixed models. RESULTS: In the blue-enriched light condition, the daily increase in median reaction time (RT), mean RT, slowest 10% of RT, and fastest 10% of RT was lower than that observed in the baseline condition between day 1 and 12 ( P ≤ 0.05). CONCLUSIONS: The addition of blue-enriched light during a long period of extended night shifts counteracts most of the daily decline in nocturnal alertness observed in the standard lighting condition, irrespectively of sleep duration and sleep efficiency.
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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 | 0.000 | 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".