Bibliographic record
Abstract
Reproductive depression is the depression in women that is related to the hormonal changes of the menstrual cycle, pregnancy and the menopause and is manifested clinically as premenstrual depression, postnatal depression and climacteric depression. These three components occur in the same vulnerable women in that a woman with depression in the menopausal transition will usually have a history of premenstrual syndrome (PMS; premenstrual dysphoric disorder [PMDD]), would have been in a good mood during pregnancy and then develop postnatal depression. When the periods return the depression becomes cyclical as PMS. These three conditions are effectively treated with transdermal estrogens which should be the first-choice therapy rather than antidepressants. Estrogens can be used together with antidepressants. The critical time to prevent long-term mood problems is the correct treatment of postnatal depression. In women with low energy and libido, often a side effect of antidepressants, the addition of transdermal testosterone is useful. These women with reproductive depression are often progesterone/progestogen intolerant and a smaller dose or duration of progestogen is a necessary compromise. Alternatively a Mirena IUS or rarely a hysterectomy is required.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.024 | 0.012 |
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".