Alcohol and Sleep I: Effects on Normal Sleep
Bibliographic record
Abstract
This review provides a qualitative assessment of all known scientific studies on the impact of alcohol ingestion on nocturnal sleep in healthy volunteers. At all dosages, alcohol causes a reduction in sleep onset latency, a more consolidated first half sleep and an increase in sleep disruption in the second half of sleep. The effects on rapid eye movement (REM) sleep in the first half of sleep appear to be dose related with low and moderate doses showing no clear trend on REM sleep in the first half of the night whereas at high doses, REM sleep reduction in the first part of sleep is significant. Total night REM sleep percentage is decreased in the majority of studies at moderate and high doses with no clear trend apparent at low doses. The onset of the first REM sleep period is significantly delayed at all doses and appears to be the most recognizable effect of alcohol on REM sleep followed by the reduction in total night REM sleep. The majority of studies, across dose, age and gender, confirm an increase in slow wave sleep (SWS) in the first half of the night relative to baseline values. The impact of alcohol on SWS in the first half of night appears to be more robust than the effect on REM sleep and does not appear to be an epiphenomenon REM sleep reduction. Total night SWS is increased at high alcohol doses across gender and age groups.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".