The Ageing Female Reproductive Axis II: Ovulatory Changes with Perimenopause
Bibliographic record
Abstract
Perimenopause, a complex physiological transition for midlife women, begins with changes in experiences many years before cycles become irregular, oestradiol levels decrease or follicle-stimulating hormone levels increase. Erratic and average higher oestradiol levels as well as shorter luteal phase lengths and lower progesterone levels occur during perimenopause. These ovarian changes may be causally related to lower inhibin production but the dynamic prospective inter-relationships within women are not well documented. This review will first define perimenopause and then explore the limited published data on ovulatory characteristics in perimenopause. In addition, it will report preliminary prospective observational data on menstrual cycles and ovulation in initially ovulatory women followed through the perimenopause. Prospective data suggest that ovulation disturbances begin early in perimenopause and increase with irregular cycles. Combined with higher oestradiol levels they may cause menorrhagia. It is not yet known whether disturbances of ovulation relate to bone loss in perimenopausal, as in premenopausal, women. It is also not known whether progesterone therapy can effectively counteract the end organ (breast, endometrial, brain) effects of higher/erratic oestradiol levels and effectively treat perimenopausal vasomotor and other symptoms.
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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 | 0.001 | 0.001 |
| 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) | 0.004 | 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".