Measuring Progress in the Management of Ambient Air Quality: The Case for Population Health
Bibliographic record
Abstract
Although progress has been made in the last few decades at reducing ambient concentrations of air pollutants, scientific evidence suggests that there remains a risk to human health from exposure to these pollutants at current levels in Canada. Much of the motivation for air pollution reduction efforts is to protect population health. This article presents a method of monitoring changes in air pollution-related health outcomes over time in conjunction with temporal changes in ambient pollution concentrations. The progress measure is a function of temporal changes in location-specific ambient concentrations and the potentially time-dependent association between those concentrations and daily deaths. The progress measure can be determined for a single location or at a national level. The measure can also be extended to include several pollutants. The progress measure is illustrated with an example of how changes in nitrogen dioxide levels in 12 Canadian cities from 1981 to 1999 have translated into changes in the percent of nonaccidental mortality burden attributable to this pollutant over time.
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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 | 0.115 | 0.176 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.009 | 0.024 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.006 | 0.010 |
| 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".