The Chemical Composition of High Arctic Snow: Deposition Mechanisms and Sources
Bibliographic record
Abstract
Recent observations of Arctic temperature increases and ice/snow loss have highlighted the importance of defining pollutant pathways to the Arctic. Fresh snow samples collected at Alert, Nunavut, from September 2014 to June 2015 were analyzed for carbon species, major ions, and metals, and their concentrations and fluxes reported. Comparison with simultaneous atmospheric monitoring found dry deposition to be a dominant removal mechanism for several compounds over the winter while wet deposition increased in importance in the fall/spring, possibly due to enhanced scavenging by mixed-phase clouds. This unprecedented dataset provided an opportunity for a temporally-refined source apportionment of key snow impurities. The majority (73%) of the black carbon in snow, a light-absorbing compound critical to the Arctic radiative balance, was identified as the product of fossil fuel burning with limited biomass burning influence. Both depositional and sourcing analyses suggested the external mixing of black carbon, sea salt, crustal, and sulphate aerosols.
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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".