Characterization of Naphthenic Acids and Other Dissolved Organics in Natural Water from the Athabasca Oil Sands Region, Canada
Bibliographic record
Abstract
With growth of the Canadian oil sands industry, concerns have been raised about possible seepage of toxic oil sands process-affected water (OSPW) into the Athabasca River (AR). A sampling campaign in fall 2015 was undertaken to monitor for anthropogenic seepage while also considering natural sources. Naphthenic acids (NAs) and thousands of bitumen-derived organics were characterized in surface water, groundwater, and OSPW using a highly sensitive online solid phase extraction-HPLC-Orbitrap method. Elevated NA concentrations and bitumen-derived organics were detected in McLean Creek (30.1 μg/L) and Beaver Creek (190 μg/L), two tributaries that are physically impacted by tailings structures. This was suggestive of OSPW seepage, but conclusive differentiation of anthropogenic and natural sources remained difficult. High NA concentrations and bitumen-derived organics were also observed in natural water located far north of the industry, including exceedingly high concentrations in AR groundwater (A5w-GW, 2000 μg/L) and elevated concentration in a tributary river (Pierre River, 34.7 μg/L). Despite these evidence for both natural and anthropogenic seepage, no evidence of any bitumen-derived organics was detected at any location in AR mainstem surface water. The chemical significance of any bitumen-derived seepage to the AR was therefore minimal, and focused monitoring in tributaries will be valuable in the future.
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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 | 0.000 | 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".