Ovulation disturbances and mood across the menstrual cycles of healthy women
Bibliographic record
Abstract
We examined the cyclicity of negative mood relative to ovulation and ovulation disturbances in Menstrual Cycle Diary(c) data collected daily during a 1-year study of ovulation, exercise, and bone change. A validated quantitative basal temperature-based methodology was used to determine the onset of the luteal phase. 'Feeling depressed', 'feeling anxious', and 'feeling angry/frustrated' were scored on a scale of 0 (absent) to 4 (very intense). Mood scores were examined over two 15-day intervals centered on either ovulation/midpoint, or on the onset of flow. Data were available from 765 cycles of 62 healthy and initially ovulatory women with a mean age of 33.9 +/- 5.4 years. Of 739 cycles that could be classified, 532 (72%) were normally ovulatory, 185 (25%) were ovulatory with a short (<10 day) luteal phase, and 22 (3%) were anovulatory. Minor cyclic mood changes were present in both ovulatory and anovulatory menstrual cycles. In anovulatory cycles, mood tended to be more variable but less negative, with a time course that differed from that in ovulatory cycles. Mood scores did not differ based on luteal phase length or with hormone levels. Patterns and mechanisms of mood change in very symptomatic women appear to be essentially amplifications of normal experiences.
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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 | 0.002 |
| 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) | 0.001 | 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".