The Effect of Arctic Dust on the Retrieval of Satellite Derived Sea and Ice Surface Temperatures
Bibliographic record
Abstract
Large quantities of dust are transported annually to the Arctic, primarily from Asian deserts. The influx of dust into the polar environment changes the radiative properties of clouds while the deposition of dust onto ice and snow decreases the surface albedo. Atmospheric and surface dust may be identified with space borne radiometers by comparing infrared energy in the 11 μm and 12 μm regime. Between 2007 and 2017 satellite infrared data revealed persistent low-level dust clouds in the vicinity of Amundsen Gulf in the Western Canadian Arctic during the melting season. Evidence suggests that the subsequent deposition of atmospheric dust in the region affected the surface emissivity in the thermal infrared regime. As a result, satellite derived sea and ice surface temperature algorithms were rendered inaccurate in these areas. Moreover, the ubiquitous nature of dust in the region may play a role in the rapidly vanishing cryosphere.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".