The Characterization and Distribution of Inorganic Chemicals in Tributary Waters of the Lower Athabasca River, Oilsands Region, Canada
Bibliographic record
Abstract
At present, there are two large industrial plants recovering oil from the lower Athabasca oil sands area and there are plans for several more mines in the area. There are environmental concerns for aquatic life in areas downstream of current and future oil sands activities. To assess and predict potential impacts of industrial activities, it is important to separate impacts from those produced by naturally occurring oil sands deposit. Studies were therefore conducted to determine whether the water quality of tributaries to the Athabasca River, which have not been impacted by anthropogenic activities, is affected by inorganic constituents resulting from flowing through reaches with natural oilsands deposit. Three tributaries, Steepbank River, Mackay River, and Ells River at upstream and downstream locations on each stream were investigated during four surveys from 1998 to 2000. In addition to some physical parameters such as pH, conductance and hardness and the major ions (calcium, magnesium, sodium, potassium, bicarbonate, chloride, sulfate, and silicates), seventeen trace metals were investigated. Some of these metals, especially iron and manganese, were of high concentrations and in some instances, particularly in a survey conducted during the spring freshets in April 1999, exceeded guidelines for the protection of aquatic life. The observed concentrations of metals seem to be of natural origin and can be used as base-line data for future assessment of anthropogenic activities in the oil sand region.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".