Bibliographic record
Abstract
Few reports provide pregnancy or birth rates for large groups of infertile couples having a comprehensive range of treatments. This model utilizes published evidence about diagnosis, treatment, the duration of treatment and the proportion of couples receiving treatment. Assisted reproduction technology treatment (ART) utilization was set arbitrarily at three levels: 3, 10 or 50% of the couples that had no live birth after conventional treatment. For each diagnosis and treatment the model estimated total live births, singleton live births and multiple live births per 10,000 couples. The overall live birth rate with non-ART treatment would be 37%, involving 3,725 live births, of which 3,478 (93%) would be singleton and 247 (7%) would be multiple. With ART utilization at 3, 10 and 50% of couples with persistent infertility in each diagnostic category, live birth rates were 39, 43 and 47% respectively, with 8, 10 and 12% multiple births. The corresponding utilization of ART would be 244, 813 and 1481 ART cycles per 10(6) population per annum. Typical management of infertility would fall short of 50% live births even with extensive utilization of ART. Underlying unknown untreatable factors remain barriers to greater overall success in the treatment of infertility.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".