Bibliographic record
Abstract
Arctic earth system is highly sensitive environmental change. Arctic warms up by 2-4 times faster than the rest of the world. Environmental changes in Arctic has a profound impact on the regional and global climate. Aerosol particles play an important role in Arctic climate system. Predicting how Arctic atmosphere will change in a warming world requires a better understanding of the state of aerosols now, as a baseline from which any predictions can be made. Motivated by this, we carried out field observations in the Arctic region during a research cruise and at ground stations. The overall aim is to improve our understanding on the sources and aerosol particles and their impact on the climate and clouds.This presentation will show preliminary results from the DY151 research cruise (May-June 2022) to the Labrador Sea and the Davis Strait. The main objectives of the cruise include:Sources and processes of aerosol particles, cloud condensation nuclei and ice nuclei Source and processes of gaseous pollutants Formation and growth mechanism of new particles Improve modelling of aerosol sources and processes in the Arctic and predict the impact of potential increase in Arctic shipping on the clouds and climate in the future Operations onboard included the measurement of atmospheric and oceanic parameters, including:size distributions of particles from 1 nm to 20 µm; gaseous pollutants such as volatile organic compounds, nitrogen oxides, HONO, HCHO, carbon monoxide, and sulphur dioxide; molecular clusters and highly oxygenated organic compounds that contribute to the formation and growth of new particles; chemical composition of aerosol particles including both organic tracers and inorganic species, and black carbon; particle mass concentrations; cloud condensation nuclei and ice nuclei concentrations; optical observations of atmospheric particles and radiation; and surface ocean chlorophyll a concentrations and routinely measured parameters onboard such as salinity. These comprehensive observations will allow to better understand (1) the emissions, sources, and oxidation of key gaseous pollutants, (2) formation and growth of new particles, (3) contribution of newly formed particles to cloud condensation nuclei, and (4) sources of aerosol particles, cloud condensation nuclei and ice nuclei.
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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 | 0.001 | 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) | 0.001 | 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".