Approach to Assessing the Effects of Aerial Deposition on Water Quality in the Alberta Oil Sands Region
Bibliographic record
Abstract
Snow cover forms a porous medium that acts as a receptor for aerially deposited polycyclic aromatic hydrocarbons (PAHs) and metals. The snowpack, acting as a temporary storage reservoir, releases contaminants accumulating over the winter during a relatively short melt period. This process could result in elevated concentrations of contaminants in melt water. Recent studies in the Alberta oil sands region have documented increases in snowpack and lake sediment concentrations; however, no studies have addressed the fate and transport of contaminants during the snowmelt period. This study describes modelling approaches that were developed to assess potential effects of aerially deposited PAHs and metals to snowpack and snowmelt water concentrations. The contribution of snowmelt to freshwater PAH concentrations is assessed using a dynamic, multi-compartmental fate model, and the contribution to metal concentrations is estimated using a mass-balance approach. The modelling approaches described herein were applied to two watersheds in the Alberta oil sands region for two planned oil sands developments. Accumulation of PAHs in a lake within the deposition zone was also modelled for comparison to observed concentrations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".