Bibliographic record
Abstract
PURPOSE OF REVIEW: To delineate the current state of evidence on the impact of night shift work on age at natural menopause. RECENT FINDINGS: The only direct evidence is from a single observational study, which indicates that women who work night shifts are at moderately higher risk for earlier menopause and that this risk is more pronounced among younger women. Underlying biological mechanisms have yet to be sufficiently substantiated. A long-held line of inquiry, most strongly propagated by the observed link between night shift work and female breast cancer, is the 'Light at Night' hypothesis, which suggests melatonin-mediated circadian disruption as a potential regulator of reproductive signaling in women. Supporting evidence is found from observations of changes in endogenous melatonin production among night working women or in response to light exposure, and corresponding changes in endogenous ovarian hormone levels and modulated menstrual patterns, among other indications of altered central ovulation-governing processes. Susceptibility to night shift work may be modified by chronotype. SUMMARY: This review summarizes the literature related to night work and ovulatory regulation in humans, prioritizing population-based evidence to provide motivation for the study of circadian disruption and night shift work as a regulator of menopausal timing.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".