Mercury photochemistry in snow and implications for Arctic ecosystems
Bibliographic record
Abstract
Mercury is a toxic and bioaccumulative environmental contaminant, which may be transported to remote regions around the world, such as the Arctic. Snowmelt is a major source of mercury to many surface water environments, but the amount of mercury in snow varies considerably. This variation is due to the balance of mercury retention and losses from snow, which is largely controlled by photochemical mechanisms controlling speciation. As such, quantifying these photochemical reaction rates and the factors affecting them will allow for the prediction of mercury speciation and movement into receiving water bodies. This will consequently improve our ability to predict exposure of aquatic organisms to mercury. This review highlights knowledge gaps in the quantification of mercury photochemical kinetics and the specific research required to advance the science of mercury photochemistry in snow, while examining the physical and chemical snowpack variables that influence snowpack mercury reactions. At present, our lack of mechanistic and kinetic knowledge of mercury reactions in snow is one of the greatest gaps preventing accurate predictions of mercury fate in regions containing seasonal snowpacks.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".