Advances in Distinguishing Groundwater Influenced by Oil Sands Process-Affected Water (OSPW) from Natural Bitumen-Influenced Groundwaters
Bibliographic record
Abstract
Abstract The objective of this study was to advance analytical methods for detecting oil sands process-affected water (OSPW) seepage from mining containments and discriminating any such seepage from the natural bitumen background in groundwaters influenced by the Alberta McMurray formation. Improved sampling methods and quantitative analyses of two groups of monoaromatic acids were employed to analyze OSPW and bitumen-affected natural background groundwaters for source discrimination. Both groups of monoaromatic acids showed significant enrichment in OSPW, while ratios of O2/O4 containing heteroatomic ion classes of acid extractable organics (AEOs) did not exhibit diagnostic differences. Evaluating the monoaromatic acids to track a known plume of OSPW-affected groundwater confirmed their diagnostic abilities. A secondary objective was to assess anthropogenically derived artificial sweeteners and per- and polyfluoroalkyl substances (PFAS) as potential tracers for OSPW. Despite the discovery of acesulfame and PFAS in most OSPW samples, trace levels in groundwaters influenced by general anthropogenic activities preclude them as individual robust tracers. However, their inclusion with the other metrics employed in this study served to augment the tiered, weight of evidence methodology developed. This methodology was then used to confirm earlier findings of OSPW migrations into groundwater reaching the Athabasca River system adjacent to the reclaimed pond at Tar Island Dyke.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".