Seasonal and longitudinal distributions of atmospheric water‐soluble dicarboxylic acids, oxocarboxylic acids, and <b>α</b>‐dicarbonyls over the North Pacific
Bibliographic record
Abstract
Abstract In order to assess the seasonal variability of atmospheric abundances of dicarboxylic acids, oxocarboxylic acids, and α‐dicarbonyls over the North Pacific and Sea of Japan, aerosol samples were collected along the longitudinal transacts during six cruises between Canada and Japan. The back trajectory analyses indicate that aerosol samples collected in winter and spring are influenced by the East Asian outflow, whereas summer and fall samples are associated with the pristine maritime air masses. Molecular distributions of water‐soluble organics in winter and spring samples show the predominance of oxalic acid (C2) followed by succinic (C4) and malonic acids (C3). In contrast, summer and fall marine aerosols are characterized by the predominance of C3 over C4. Concentrations of dicarboxylic acids were higher over the Sea of Japan than the North Pacific. With a lack of continental outflow, higher concentrations during early summer are ascribed to atmospheric oxidation of organic precursors associated with high biological activity in the North Pacific. This interpretation is further supported by the high abundances of azelaic acid, which is a photochemical oxidation product of biogenic unsaturated fatty acids, over the Bering Sea in early summer when surface waters are characterized by high biological productivity. We found higher ratios of oxalic acid to pyruvic and glyoxylic acids (C2/Pyr and C2/ωC2) and glyoxal and methylglyoxal (C2/Gly and C2/MeGly) in summer and fall than in winter and spring, suggesting a production of C2 from the aqueous‐phase oxidation of oceanic isoprene. In this study, dicarboxylic acids account for 0.7–38% of water‐soluble organic carbon.
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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 | 0.000 | 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".