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Systems for rating bodies of evidence used in systematic reviews of air pollution exposure and reproductive and children’s health: a methodological survey

2024· other· en· W6977471544 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typeother
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsGrading (engineering)OperationalizationSystematic reviewRating scaleRating systemPublic healthEvidence-based practiceExposure assessment

Abstract

fetched live from OpenAlex

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.

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

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 armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Evaluation · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptMetaresearch
Domain: Methods · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.710
metaresearch head score (Gemma)0.875
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.290
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7100.875
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0130.021
Bibliometrics0.0810.074
Science and technology studies0.0050.011
Scholarly communication0.0190.013
Open science0.0080.021
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.280
GPT teacher head0.360
Teacher spread0.080 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
DomainEvaluation · Methods
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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