Molecular Marker Study of Particulate Organic Matter in Southern Ontario Air
Bibliographic record
Abstract
To study the origins of airborne particulate organic matter in southern Ontario, molecular marker concentrations were studied at Hamilton, Simcoe, and York Gateway Tunnel, representing industrial, rural, and heavy traffic sites, respectively. Airborne particulate matter smaller than 10 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>μ</mml:mi></mml:mrow></mml:math>m in aerodynamic diameter was collected on quartz filters, and the collected samples were analyzed for total carbons, 5-6 ring PAHs, hopanes, n -alkanes (C 20 to C 34 ), and oxygenated aromatic compounds. Results showed that PAH concentrations at all three sites were highly correlated, indicating vehicular emissions as the major source. Meanwhile, in the scatter plots of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:mi>α</mml:mi></mml:mrow></mml:math>,<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mrow><mml:mi>β</mml:mi></mml:mrow></mml:math>-hopane and trisnorhopane, concentrations displayed different trends for Hamilton and Simcoe. The slopes of the linear regressions for Hamilton and the tunnel were statistically the same, while the slope for Simcoe was significantly different from those. Comparison with literature values revealed that the trend observed at Simcoe was explained by the influence from coal combustion. We also found that the majority of oxygenated aromatic compounds at both sites were in the similar level, possibly implying secondary products contained in the southern Ontario air. Regardless of some discrepancies, absolute principal component analysis applied to the datasets could reproduce those findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".