Aerosol composition and sources in the central Arctic Ocean during ASCOS
Bibliographic record
Abstract
Abstract. Measurements of submicron aerosol chemical composition were made over the central Arctic Ocean from 5 August to 8 September 2008 as a part of the Arctic Summer Cloud Ocean Study (ASCOS) using an aerosol mass spectrometer (AMS). The median levels of sulphate and organics for the entire study were 0.051 and 0.055 μ g m−3, respectively. Positive matrix factorisation was performed on the entire mass spectral time series and this enabled marine biogenic and continental sources of particles to be separated. These factors accounted for 33% and 36% of the sampled ambient aerosol mass, respectively, and they were both predominantly composed of sulphate, with 47% of the sulphate apportioned to marine biogenic sources and 48% to continental sources, by mass. Within the marine biogenic factor, the ratio of methane sulphonate to sulphate was 0.25 ± 0.02, consistent with values reported in the literature. The organic component of the continental factor was more oxidised than that of the marine biogenic factor, suggesting that it had a longer photochemical lifetime than the organics in the marine biogenic factor. The remaining ambient aerosol mass was apportioned to an organic-rich factor that could have arisen from a combination of marine and continental sources. In particular, given that the factor does not correlate with common tracers of continental influence, we cannot rule out that the organic factor arises from a primary marine source.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".