Physical Characterization of the University of Toronto Coarse, Fine, and Ultrafine High-Volume Particle Concentrator Systems
Bibliographic record
Abstract
Particle concentrators allow exposure to controlled levels of concentrated ambient particulate matter (PM) over a broad range of concentrations. The performance of these systems can be influenced by the physicochemical characteristics of PM and so it is vital to characterize the concentrators at a given site. The quasi-ultrafine PM (<0.2 μm), fine PM (0.15–2.5 μm), and coarse PM (2.5–10 μm) concentrators at the Southern Ontario Center for Atmospheric Aerosol Research (SOCAAR), University of Toronto, were characterized as a part of the “Health Effects of Aerosols in Toronto (HEAT)” campaign held during February–March, 2010. The full size distributions of ambient and concentrated particles were simultaneously measured in terms of number, surface area, and volume using high time-resolution instruments. Examination of the complete size distribution, including the unconcentrated particles beyond the cutpoints of the concentrator systems, revealed that particles in the unconcentrated size ranges made significant contributions to the particle number and surface area present in the concentrated airstreams of fine and coarse concentrators. Further transients in the ambient ultrafine particle concentrations were evident as dampened signals in these concentrated airstreams. The ultrafine concentrator exhibited a significant size shift when the ambient particle size distribution had a mode ≤30 nm. Overall the fine and coarse concentrators provided a reasonable concentrated reproduction of the ambient PM mass while questions remain regarding the representativeness of the ultrafine concentrator.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".