Phytoplankton blooms weakly influence the cloud forming ability of sea spray aerosol
Bibliographic record
Abstract
Abstract After many field studies, the establishment of connections between marine microbiological processes, sea spray aerosol (SSA) composition, and cloud condensation nuclei (CCN) has remained an elusive challenge. In this study, we induced algae blooms to probe how complex changes in seawater composition impact the ability of nascent SSA to act as CCN, quantified by using the apparent hygroscopicity parameter ( κ app ). Throughout all blooms, κ app ranged between 0.7 and 1.4 (average 0.95 ± 0.15), consistent with laboratory investigations using algae‐produced organic matter, but differing from climate model parameterizations and in situ SSA generation studies. The size distribution of nascent SSA dictates that changes in κ app associated with biological processing induce less than 3% change in expected CCN concentrations for typical marine cloud supersaturations. The insignificant effect of hygroscopicity on CCN concentrations suggests that the SSA production flux and/or secondary aerosol chemistry may be more important factors linking ocean biogeochemistry and marine clouds.
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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) | 0.001 | 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".