Counseling lesbian patients about getting pregnant.
Bibliographic record
Abstract
OBJECTIVE: To describe an approach to counseling lesbian patients about getting pregnant. SOURCES OF INFORMATION: Information in this paper is based on evidence from randomized controlled trials (level I evidence), non-randomized trials (level II evidence), expert opinion (level III evidence), and government regulations. MAIN MESSAGE: We review 5 steps that comprise an approach to counseling lesbian patients about getting pregnant safely and efficiently. These steps are preconception care (including counseling, testing, and immunization); donor choice (including explaining the risks and benefits of choosing between a known or anonymous donor and the difference between fresh and frozen semen); donor testing (including Health Canada's requirements for semen processing and recommendations for testing before home insemination); ordering the semen (including information about sperm banks and the need for "Canadian compliant" semen); and the insemination process (including techniques for monitoring ovulation and various methods of insemination). CONCLUSION: Primary care physicians can help lesbians achieve pregnancy by providing education, testing, referrals, and insemination services.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".