Frost flowers growing in the Arctic ocean‐atmosphere–sea ice–snow interface: 2. Mercury exchange between the atmosphere, snow, and frost flowers
Bibliographic record
Abstract
Frost flowers are ice crystals that grow on refreezing sea ice leads in Polar Regions by wicking brine from the sea ice surface and accumulating vapor phase condensate. These crystals contain high concentrations of mercury (Hg) and are believed to be a source of reactive halogens, but their role in Hg cycling and impact on the fate of Hg deposited during atmospheric mercury depletion events (AMDEs) are not well understood. We collected frost flowers growing on refreezing sea ice near Barrow, Alaska (U.S.A.) during an AMDE in March 2009 and measured Hg concentrations and Hg stable isotope ratios in these samples to determine the origin of Hg associated with the crystals. We observed decreasing Δ199Hg values in the crystals as they grew from new wet frost flowers (mean Δ199Hg = 0.77 ± 0.13‰, 1 s.d.) to older dry frost flowers (mean Δ199Hg = 0.10 ± 0.05‰, 1 s.d.). Over the same time period, mean Hg concentrations in these samples increased from 131 ± 6 ng/L (1 s.d.) to 180 ± 28 ng/L (1 s.d.). Coupled with a previous study of Hg isotopic fractionation during AMDEs, these results suggest that Hg initially deposited to the local snowpack was subsequently reemitted during photochemical reduction reactions and ultimately accumulated on the frost flowers. As a result of this process, frost flowers may lead to enhanced local retention of Hg deposited during AMDEs and may increase Hg loading to the Arctic Ocean.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".