Bibliographic record
Abstract
INTRODUCTION: Semen analysis norms have been serially calculated by the World Health Organization and have decreased at each reassessment. In 2010, these norms were based on fertile males for the first time. The goal of this study is to assess whether the latest 2010 semen analysis parameters are better predictors of intrauterine insemination success than the 1999 limits. METHODS: A retrospective cohort study was performed over a 2.5-year period at the Stanford Fertility Center. Semen samples were classified based on individual semen parameters: normal by all 1999 parameters (“N. 1999”), abnormal by at least one 1999 parameter but normal by 2010 parameters (“AbN. 1999/N. 2010”), or abnormal by at least one 2010 parameter (“AbN. 2010”). Outcomes were compared using correlation coefficients and χ2 tests. RESULTS: A total of 2,231 intrauterine insemination cycles from 981 couples were included. No significant correlation between the semen grouping and pregnancy likelihood was demonstrated (r=−0.25, P=.24). Pregnancy rates were similar for the N. 1999 (22%), AbN. 1999/N. 2010 (22%), and AbN. 2010 (20%). Even after adjusting for possible confounders, significance was not reached: comparison of N. 1999 with AbN. 1999/N. 2010 (P=.25), comparison of N. 1999 with AbN. 2010 (P=.26), and comparison of AbN. 1999/N. 2010 with AbN. 2010 (P=.93). Confounders evaluated included maternal age, duration of infertility, number of previous pregnancies and of mature follicles, and maximum day 3 follicle-stimulating hormone levels. CONCLUSION: Serially updating semen analysis norms has little clinical implication in the infertile population when related to intrauterine insemination.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".