A characterization of Arctic aerosols on the basis of aerosol optical depth and black carbon measurements
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Aerosols, transported from distant source regions, influence the Arctic surface radiation budget. When deposited on snow and ice, carbonaceous particles can reduce the surface albedo, which accelerates melting, leading to a temperature-albedo feedback that amplifies Arctic warming. Black carbon (BC), in particular, has been implicated as a major warming agent at high latitudes. BC and co-emitted aerosols in the atmosphere, however, attenuate sunlight and radiatively cool the surface. Warming by soot deposition and cooling by atmospheric aerosols are referred to as “darkening” and “dimming” effects, respectively. In this study, climatologies of spectral aerosol optical depth AOD (2001–2011) and Equivalent BC (EBC) (1989–2011) from three Arctic observatories and from a number of aircraft campaigns are used to characterize Arctic aerosols. Since the 1980s, concentrations of BC in the Arctic have decreased by more than 50% at ground stations where in situ observations are made. AOD has increased slightly during the past decade, with variations attributed to changing emission inventories and source strengths of natural aerosols, including biomass smoke and volcanic aerosol, further influenced by deposition rates and airflow patterns.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 |
| 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 it