Air pollution in the city of Prince George: Chemical analysis of particulate matter (PM2.5) contaminants
Bibliographic record
Abstract
Air pollution has been an ongoing issue for the City of Prince George, the largest city in northern British Columbia. This research was designed to measure the chemical composition of atmospheric Particulate Matter (PM2.5) in a Prince George neighborhood (i.e., downtown). The main objective of this research was to determine the PM2.5 chemical compositions in two distinct periods: warm and cold. Overall, 153 samples were collected from January to August 2018, using personal air samplers. The highest concentration of PM2.5 was recorded during the 2018 summer wildfires. Chemical composition of the PM2.5 air samples were studied with respect to Cadmium, Potassium, Mercury, Sodium, Lead, Chromium, Iron, Cobalt, Nickel, Manganese, Copper, Titanium, Molybdenum, Phosphorus and Sulphur, in order to evaluate potential sources of air pollutants in the city. The results of this study were compared with PM2.5 averages from other Canadian and international cities. The possibilities of the contribution of some local industrial sources such as pulp and paper, biomass burning, transportation and road dust, on PM2.5 concentration and chemical composition were discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".