Spatial and environmental impacts on adverse birth outcomes in Ontario
Bibliographic record
Abstract
This study assesses the overall spatial variations and neighbourhood‐level “hot spots” of low birth weight and preterm birth incidence within three public health units in Ontario, Canada. The analysis uses a stepwise approach of intra‐class correlation analysis, a spatial scan statistic, and multilevel spatial modeling. Results show that neighbourhood level variation accounts for only 2–3 percent of the total variation of adverse birth outcomes in the study area. However, strong spatial autocorrelation is observed at the neighbourhood level, and spatial clusters of relatively high adverse birth outcome rates exist in areas that are associated with environmental risks, including pollution sources and proximity to highways. Thus, although estimated neighbourhood impacts on adverse birth outcomes are small compared with those of individual‐level risks, local high potential environmental risk areas are identifiable. Environmental surveillance and spatial statistical analysis should be conducted regularly by local health authorities to identify and monitor the impact of environmental changes on health in general and on birth outcomes in particular. Specific community‐oriented health interventions may be required to reduce observed local health impacts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".