Potential dangers in the customary methods of conducting meta-analyses: Lack of bias in the meta-analysis of recombinant versus urinary follicle stimulating hormone
Bibliographic record
Abstract
In a meta-analysis of randomized trials comparing recombinant and urinary FSH for ovarian stimulation in infertility treatment cycles, the clinical pregnancy rate per cycle started was significantly higher with recombinant FSH. Before the results of the different trials can be pooled, it is important to determine whether the results are homogeneous so that one can obtain an overall treatment estimate that is without bias. There are several methods to ascertain lack of homogeneity, including logistic regression analysis, sensitivity analysis comparing fixed-effect and random-effect models, testing based in the chi2 distribution, and graphical methods comparing event rates in experimental and treatment groups. These methods all confirmed that the treatment effect was homogeneous across all trials thereby providing assurance that the overall conclusion of the superior efficacy of recombinant FSH compared with urinary FSH is based on an unbiased analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".