Human Exposure to Polychlorinated Biphenyls (PCBs) and The Risk of Endometriosis: A Systematic Review and Meta-Analysis Protocol
Bibliographic record
Abstract
Endometriosis is one of the gynecological disorders and its prevalence is estimated to 8.10% of reproductive-age women. In Iran, the frequency of endometriosis was reported at 29% among infertile women. The etiology of endometriosis is still unclear. Numerous environmental contaminants such as polychlorinated biphenyls (PCBs) may play important roles in endometriosis development and etiology. Iranian population has relatively low levels of PCBs. However, no studies have evaluated PCBs levels in Iranian endometriosis patients so far. At present, there is no systematic review of the relationship between only PCBs exposure and the risk of endometriosis. The aim of this systematic review and meta-analysis protocol will be to evaluate the association between only PCBs exposure and the risk of endometriosis. PubMed/MEDLINE, Web of Science, Scopus, Google Scholar, Embase, key journals, conferences/congress research papers, and the references of included primary studies will be searched. Observational studies (cross-sectional, case-control, and cohort) in humans that investigated the association between PCBs exposure and the risk of endometriosis will be included. The outcome will be endometriosis risk in association with PCBs exposure. The primary screening and data extraction will be performed by three team members independently and will be judged by opinion with the fourth member. The modified Newcastle-Ottawa Scale (NOS) will be used for the quality assessment of studies. Findings from this study will recognize the association between PCBs exposure and the risk of endometriosis. Results may provide a new window for identifying the role of PCBs as environmental risk factors in relation to the development of endometriosis. Registration number: PROSPERO; CRD42019120539
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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 | 0.048 | 0.067 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.024 | 0.023 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.049 | 0.004 |
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".