The hygroscopicity parameter (κ) of ambient organic aerosol at a field site subject to biogenic and anthropogenic influences: Relationship to degree of aerosol oxidation
Bibliographic record
Abstract
Abstract. Cloud condensation nuclei (CCN) concentrations were measured at a rural site in Ontario, Canada during the spring of 2007. The CCN concentrations were compared to values predicted from the aerosol chemical composition and size distribution using κ-Köhler theory. The hygroscopicity of the organic component was characterised by two methods, both of which are based on the aerosol's degree of oxygenation as determined by the mass spectra measured with an Aerodyne aerosol mass spectrometer. The first approach uses a statistical technique, positive matrix factorization (PMF), to separate hygroscopic and non-hygroscopic factors while the second uses the O/C, which is an indication of the aerosol's degree of oxygenation. In both cases, the hygroscopicity parameter (κ) of the organic component is varied so that the predicted and measured CCN concentrations are internally consistent and in good agreement. By focussing on a small number of organic components defined by their composition, we can simplify the estimates needed to describe the aerosol's hygroscopicity. We find that κ of the oxygenated organic component from the PMF analysis is 0.20±0.03 while κ of the entire organic component can be parameterized as κorg=(0.30±0.05)×(O/C).
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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 | 0.000 | 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 | 0.000 |
| 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 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".