Systems for rating bodies of evidence used in systematic reviews of air pollution exposure and reproductive and children’s health: a methodological survey
Bibliographic record
Abstract
Abstract Background Translating findings from systematic reviews assessing associations between environmental exposures and reproductive and children’s health into policy recommendations requires valid and transparent evidence grading. Methods We aimed to evaluate systems for grading bodies of evidence used in systematic reviews of environmental exposures and reproductive/ children’s health outcomes, by conducting a methodological survey of air pollution research, comprising a comprehensive search for and assessment of all relevant systematic reviews. To evaluate the frameworks used for rating the internal validity of primary studies and for grading bodies of evidence (multiple studies), we considered whether and how specific criteria or domains were operationalized to address reproductive/children’s environmental health, e.g., whether the timing of exposure assessment was evaluated with regard to vulnerable developmental stages. Results Eighteen out of 177 (9.8%) systematic reviews used formal systems for rating the body of evidence; 15 distinct internal validity assessment tools for primary studies, and nine different grading systems for bodies of evidence were used, with multiple modifications applied to the cited approaches. The Newcastle Ottawa Scale (NOS) and the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework, neither developed specifically for this field, were the most commonly used approaches for rating individual studies and bodies of evidence, respectively. Overall, the identified approaches were highly heterogeneous in both their comprehensiveness and their applicability to reproductive/children’s environmental health research. Conclusion Establishing the wider use of more appropriate evidence grading methods is instrumental both for strengthening systematic review methodologies, and for the effective development and implementation of environmental public health policies, particularly for protecting pregnant persons and children.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Metaresearch Domain: Methods · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".