Sources of Methylmercury to Snowpacks of the Alberta Oil Sands Region: A Study of In Situ Methylation and Particulates
Bibliographic record
Abstract
Snowpacks in the Alberta Oil Sands Region (AOSR) of Canada contain elevated loadings of methylmercury (MeHg; a neurotoxin that biomagnifies through foodwebs) due to oil sands related activities. At sites ranging from 0 to 134 km from the major AOSR upgrading facilities, we examined sources of MeHg by quantifying potential rates of MeHg production in snowpacks and melted snow using mercury stable isotope tracer experiments, as well as quantifying concentrations of MeHg on particles in snowpacks (pMeHg). At four sites, methylation rate constants were low in snowpacks ( k m = 0.001–0.004 d –1 ) and nondetectable in melted snow, except at one site ( k m = 0.0007 d –1 ). The ratio of methylation to demethylation varied between 0.3 and 1.5, suggesting that the two processes are in balance and that in situ production is unlikely an important net source of MeHg to AOSR snowpacks. pMeHg concentrations increased linearly with distance from the upgraders (R 2 = 0.71, p < 0.0001); however, snowpack total particle and pMeHg loadings decreased exponentially over this same distance (R 2 = 0.49, p = 0.0002; R 2 = 0.56, p < 0.0001). Thus, at near-field sites, total MeHg loadings in snowpacks were high due to high particle loadings, even though particles originating from industrial activities were not MeHg rich compared to those at remote sites. More research is required to identify the industrial sources of snowpack particles in the AOSR.
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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 | 0.001 | 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".