Bibliographic record
Abstract
Abstract In this chapter the authors discuss sex differences in sleep behavior, sleep structure, and aspects of three sleep disorders. Women report a greater need for sleep and sleep longer than men, as determined from self-report as well as actigraphy and wearable sleep trackers, although this difference is heavily influenced by family and work responsibilities. Women are also more likely to have earlier bedtimes and a morning chronotype, which may in part be a consequence of their phase-advanced circadian rhythms and shorter circadian period compared with men. Women are more likely than men to report poorer sleep quality and greater difficulty sleeping; however, polysomnographic recordings reveal other sex differences, including better sleep efficiency and more slow-wave sleep that is better preserved with aging in women than in men. Sex differences are evident in the prevalence, presentation, and etiology of some sleep disorders. Women are more likely than men to have insomnia disorder, a difference that becomes evident in adolescence and continues across the life span. Restless legs syndrome is more prevalent in women than men, and they also experience worse symptoms, particularly during pregnancy and postmenopause. Men are at greater risk for obstructive sleep apnea, at least until women reach menopause, when the sex difference lessens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.006 |
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".