Bibliographic record
Abstract
The androgen milieu and sexual desire in women seem to be tightly linked because they both decline with age. However, we are still missing a cut-off plasma level for androgens (total testosterone, free testosterone) or androgen precursors (androstenedione, dehydroepiandrosterone (DHEA) and DHEA sulfate (DHEAS)) to diagnose androgen deficiency in clinical practice. Apart from the complex multidimensional nature of sexual desire across the reproductive lifespan, the correlation between measurements of testosterone and specific signs and symptoms has been difficult because, according to guidelines, most available assays are unreliable at baseline and under hormonal treatments. Recent data obtained with accurate methods based on mass spectrometry to measure total testosterone levels found a significant positive association with sexual desire, arousal and masturbation in midlife US women across the menopausal transition. Even in a European cohort of healthy women aged 19-65 years, sexual desire, measured with a validated questionnaire, correlated overall with free testosterone and androstenedione measured with mass spectrometry. Collectively, these data support the therapeutic use of testosterone for low desire and sexual dysfunction in those clinical conditions in which androgen deficiency may be accurately diagnosed.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.020 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.012 |
| 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".