Nickel geochemistry of oil sands fluid petroleum coke deposits, Alberta, Canada
Bibliographic record
Abstract
Nickel (Ni) leaching from oil sands petroleum coke can have toxicological effects on aquatic organisms. However, geochemical controls on Ni release, transport, and attenuation within coke deposits remains limited. We examined the geochemistry of fluid coke and associated pore waters from two deposits at an oil sands mine near Fort McMurray, Alberta, Canada. Synchrotron-based micro-X-ray fluorescence (μXRF) and micro-X-ray absorption near edge structure (μXANES) spectroscopy show that Ni(II)-porphyrin complexes dominate, but inorganic phases including Ni(II)-sulfide and Ni(II)-oxide comprise a minor component of fluid coke. Sequential chemical extractions suggested that sorption–desorption reactions may influence Ni mobility within fluid coke deposits. Although only a small proportion of total Ni (<4%) is susceptible to leaching under environmentally relevant concentrations, dissolved Ni concentrations ( n = 65) range from 2 to 120 μg·L−1 (median 7.8 μg·L−1) within the two deposits and generally decrease with depth below the water table. Pore water Ni concentrations are negatively correlated with pH, but not with dissolved sulfate, bicarbonate, or chloride. Overall, our findings suggest that pore water pH and sorption–desorption reactions are principal controls on dissolved Ni concentrations within oil sands fluid petroleum coke deposits.
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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".