Spatial Variability of Ambient Nitrogen Dioxide and Sulfur Dioxide in Sarnia, “Chemical Valley,” Ontario, Canada
Bibliographic record
Abstract
This study aimed at developing models to predict nitrogen dioxide (NO(2)) and sulfur dioxide (SO(2)) concentrations in Sarnia, "Chemical Valley", Ontario, Canada, and model the intra-urban variation of ambient NO(2) and SO(2) in the city for a community health study. NO(2) and SO(2) samples were monitored with Ogawa passive samplers at 39 locations across the city for 2 wk during the fall of 2005. The final land use regression models were constructed to generate independent variables that might best predict NO(2) and SO(2) concentrations. The coefficients of determinations for the final NO(2) and SO(2) models were .79 and .66, respectively. The explanatory variables in the final NO(2) model were: proximity to the industrial core, industrial areas within 1600 m, highways within 400 m, and dwelling counts within 2400 m. The variables in the final SO(2) model were: proximity to the industrial core, industrial areas within 1200 m, and major roads within 100 m. The spatial variations captured in these analyses are being used to estimate ambient pollution concentrations for a large health study.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".