Bibliographic record
Abstract
Abstract Groundwater discharges in the western Canadian oil sands region impact river water quality. Mapping groundwater discharges to rivers in the oil sands region is important to target water quality monitoring efforts and to ensure injected wastewater and steam remain sequestered rather than eventually resurfacing. Saline springs composed of Pleistocene‐aged glacial meltwater exist in the region, but their spatial distribution has not been mapped comprehensively. Here we show that formation waters discharge into 3 major rivers as they flow through the Athabasca Oil Sands Region adjacent to many active oil sands projects. These discharges increase river chloride concentrations from river headwaters to downstream reaches by factors of ~23 in the Christina River, ~4 in the Clearwater River, and ~5 in the Athabasca River. Our survey provides further evidence for the substantial impact of formation water discharges on river water quality, even though they comprise less than ~2% of total streamflow. Geochemical evidence supporting formation water discharges as the leading control on river salinity include increases in river chloride concentrations, Na/(Na + Ca) ratios, Cl/(Cl + SO4) ratios and decreases in 87Sr/86Sr ratios; each mixing trend is consistent with saline groundwater discharges sourced from Cretaceous or Devonian aquifers. These regional subsurface‐to‐surface connections signify that injected wastewater or steam may potentially resurface in the future, emphasizing the critical importance of mapping groundwater flow paths to understand present‐day streamflow quality and to predict the potential for injected fluids to resurface.
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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 | 0.002 |
| 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) | 0.002 | 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".