Can We Monitor Snow Properties on Sea Ice to Investigate Its Role in Tropospheric Ozone Depletion?
Bibliographic record
Abstract
Abstract In the lower troposphere over the Arctic Ocean, ozone is often destroyed in spring by chemical chain reactions involving the reactive bromine species Br and BrO. The role of surface snow in generating reactive bromine has been suspected, but many details of the processes not understood. Using unique data such as BrO concentrations from instruments on buoys, Burd et al. (2017, https://doi.org/10.1002/2017JD026906) observed that the snowmelt onset date often coincides with the end of the reactive bromine season. They proposed that the decrease in snow‐specific surface area and/or the occurrence of liquid water in snow induced by melting dramatically slows the rate of surface reactions generating bromine, indicating that the physical state of the snow is critical for bromine generation. Their suggestion is discussed, and a method to test it using novel instrumentation recently available is proposed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".