Success of In Vitro Fertilization: A Researched Science or a Performance Indicator
Bibliographic record
Abstract
Divisions of reproductive medicine often perceive the live birth rate (LBR) as the single most important performance indicator for any infertility clinic, and it reflects on the quality of their services. Due to this perception, some infertility experts might refrain from disclosing these rates in publications as a researched science. Infertility experts might not be familiar with the various methods of reporting LBR as an outcome of in vitro fertilization (IVF) and therefore should be aware of these methods. Moreover, infertility experts might miss to take into account some couple and disease-related characteristics that could be successful determinants of this LBR. This is a brief review on infertility and its impact on married couples, as well as the history and description of IVF. We also present infertility experts with various methods of reporting LBR and shed light on some of the couple and disease-related factors associated with higher LBRs after IVF as reported in literature. J Clin Gynecol Obstet. 2017;6(3-4):53-57 doi: https://doi.org/10.14740/jcgo458w
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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 | 0.015 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".