Regional ground‐level ozone trends in the context of meteorological influences across Canada and the eastern United States from 1997 to 2006
Bibliographic record
Abstract
Meteorologically adjusted trends for different ozone averaging metrics (including daily maximum 1 h, daily maximum 8 h average, daily average, daytime average, nighttime average, daily minimum 8 h average, and monthly 5th percentile of ozone mixing ratios) were investigated in different regions of Canada and the United States over the time period 1997–2006. The spatiotemporal variability of the May–September daily ozone mixing ratios from 97 nonurban ozone measurement sites in Canada and the United States was examined to establish regions of common variability using rotated principal component analysis (R‐PCA). This was followed by modeling multiple sites within the PCA‐derived regions for all months using generalized linear mixed models. Most regions in southeastern Canada and the eastern United States showed statistically significant decreasing trends in the daily maximum 8 h average ranging from 0.53 ± 0.2 to 2.7 ± 0.86%/a, whereas significant increasing trends of 0.44 ± 0.37%/a and 0.98 ± 0.76%/a were found in Atlantic and Pacific Canada, respectively. In southeastern Canada and the eastern United States, the rates of decrease of the meteorologically adjusted regional trends associated with low ozone levels were slower than those of high levels. However, the rates of increase in the Atlantic and Pacific coastal regions associated with low levels were faster than those of high levels. These results are consistent with decreasing NOx and nonmethane hydrocarbon emissions in southeastern Canada and the eastern United States starting in the early 2000s and a hypothesized widespread increase due to the rising hemispheric background ozone.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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".