Maternal Arsenic Exposure and Gestational Diabetes: A Systematic Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Gestational diabetes mellitus (GDM) is a metabolic complication associated with adverse outcomes for mother and fetus. Arsenic (As) exposure has been suggested as a possible risk factor for its development. The aim of this meta-analysis was to provide a comprehensive overview of published evidence on the association between As and GDM. The systematic search from PubMed, MEDLINE, and Scopus was limited to full-length manuscripts published in peer-reviewed journals up to April 2020, identifying fifty articles. Ten studies met the inclusion criteria, nine for quantitative synthesis with a total of n = 1984 GDM cases. The overall pooled risk was 1.56 (95% Confidence Interval - CI = 1.23, 1.99) with moderate heterogeneity (χ2 = 21.95; I2% = 64). Several differences among the included studies that may account for heterogeneity were investigated. Stratification for exposure indicator confirmed a positive association for studies assessing urine As. A slightly higher risk was detected pooling studies based in Asia rather than in North America. Stratification for GDM diagnostic criteria showed higher risks when diagnosis was made according to the Canadian Diabetes Association (CDA-SOGC) or World Health Organization (WHO) criteria, whereas a lower risk was observed when adopting the American Diabetes Association (ADA) criteria. These results provide additional evidence for a possible association between As exposure and GDM, although the data need to be interpreted with caution due to heterogeneity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it