Inventory of aerosol episodes in Ny-Ålesund (Svalbard) in the period 2017-2020 by sun photometry
Bibliographic record
Abstract
Atmospheric aerosols are an important forcing agent in the estimation of radiative budget, being the Arctic an area of special weakness. The Group of Atmospheric Optics, University of Valladolid and the Alfred Wegener Institute for Polar and Marine Research, installed in 2017 a CE-318T Sun-sky-Moon photometer (Cimel Electronique S.A.S) in the Arctic station Ny-Ålesund (79ºN, 12ºE). This study presents an inventory of all high-turbidity aerosol episodes recorded in the period 2017-2020 (data of level 1.5-validated from AERONET). This inventory is based on the separate analysis of coarse and fine mode aerosol optical depth. Aerosol episodes are attributed to coarse, fine or mixture of aerosols. Complementary information provided by HYSPLIT air mass back trajectories, MODIS images, forecast aerosol models, CALIOP/CALIPSO satellite data, and other collocated instruments on the station are also used. Special focus is given to long-range transport of aerosols from big forest fires in Canada, United States and Russia.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 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".