Genotoxicity of Prenatal and Early Childhood Exposure to Pesticides: A Protocol and Pilot Study of a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
1. Abstract Objectives To systematically review and meta-analyse the genotoxic impact of prenatal and early childhood pesticide exposure, investigating prevalence, specific pesticides, effect size, mechanisms, genetic susceptibility, and vulnerable periods. Study Design A protocol for systematic review and meta-analysis. A pilot study was also conducted to develop appropriate extraction and risk of bias tool. Methods Adhering to 2020 PRISMA guidelines, the review will explore genotoxic impact of prenatal and early childhood pesticide exposure in children up to 5 years. The protocol had been registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (CRD42024510877). Searches was done across PubMed, EMBASE, Web of Science, and Scopus use keywords ‘prenatal or childhood’, ‘pesticides’, and ‘genotoxicity’. Manual reference screening supplements searches. Eligible observational studies (cross-sectional, case-control, cohort designs) in English will be included, while excluding case reports and in vitro studies, using Covidence screening tool. Two independent reviewers will use Newcastle-Ottawa Scale and novel tool for cross-sectional studies for screening, data extraction, and risk of bias assessment. Findings will be synthesized narratively, with potential meta-analysis of genotoxicity outcomes. GRADE approach will assess the evidence quality. Results A pilot test screened 1,405 studies, resulting in 21 eligible for full-text screening. Twelve were excluded. Data extraction and risk of bias assessment followed pre-defined protocols. Findings informed the refinement of study procedures. Conclusions The protocol outlines a comprehensive approach to systematically review the genotoxic impact of prenatal and early childhood pesticide exposure, aiming to provide necessary insights to a better understanding of this environmental risk.
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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 | 0.116 | 0.182 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.015 | 0.019 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.057 | 0.008 |
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".