Stable isotope method for tracing oil sands bitumen sources, differentiating δ13C in four carbon fractions in water and acid-extractable organics
Bibliographic record
Abstract
This study was conducted at an oil-sands operation in the North Athabasca Oil Sands Region, Alberta, Canada to identify suitable isotopic tracers for differentiating between processed (anthropogenic) and non-processed bitumen residues in water. A combination of isotopes of water, solutes, and acid-extractable organics (AEO) were measured in tailings ponds containing oil-sands process water (OSPW), groundwater from the basal McMurray Formation, and a variety of on-lease groundwater monitoring wells and mitigation structures, the latter designed to intercept potentially contaminated runoff. This study provides supporting evidence that tailings ponds are well-contained and are not hydraulically connected with monitoring wells in local Quaternary aquifers or underlying formations at the investigated site. Testing included individual isotopic tracers and dual isotope pairs, as well as comprehensive suites of both isotopes and naphthenic-acid (NA) species. An isotopic approach using δ 13 C in four distinct carbon fractions emerges from our assessment as a promising method for operational fingerprinting of processed and non-processed bitumen residues in water for tracking potential OSPW seepage at oil sands operations.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".