Apparent Temperature and Air Pollution vs. Elderly Population Mortality in Metro Vancouver
Bibliographic record
Abstract
BACKGROUND: Meteorological conditions and air pollution in urban environments have been associated with general population and elderly mortality, showing seasonal variation. OBJECTIVES: This study is designed to evaluate the relationship between apparent temperature (AT) and air pollution (PM₂.₅) vs. mortality in elderly population of Metro Vancouver. METHODS: Statistical analyses are performed on moving sum daily mortality rates vs. moving average AT and PM₂.₅ in 1-, 2-, 3-, 5-, and 7-day models for all seasons, warm temperatures above 15°C, and cold temperatures below 10°C. RESULTS: Approximately 37% of the variation in all-season mortality from circulatory and respiratory causes can be explained by the variation in 7-day moving average apparent temperature (r² = 0.37, p<0.001). Although the analytical results from air pollution models show increasingly better prediction ability of longer time-intervals (r² = 0.012, p<0.001 in a 7-day model), a very weak negative association between elderly mortality and air pollution is observed. CONCLUSIONS: Apparent temperature is associated with mortality from respiratory and circulatory causes in elderly population of Metro Vancouver. In a changing climate, one may anticipate to observe potential health impacts from the projected high- and particularly from the low-temperature extremes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".