Effects of Calcium and Aluminum on Particle Settling in an Oil Sands End Pit Lake
Bibliographic record
Abstract
Abstract Surface mining of oil sands ore in Alberta, Canada has generated fluid fine tailings (FFT) that must be reclaimed. End pit lakes (EPLs), which consist of thick deposits of FFT capped with water, have been proposed for FFT reclamation, and Base Mine Lake (BML) is the first full-scale demonstration EPL. However, FFT particle settling and resuspension contributes to high turbidity in the BML water cap, which may be detrimental to the development of an aquatic ecosystem. This study investigated the effect of Ca and Al treatments on turbidity mitigation. The initial turbidity was reduced from 20 NTU to less than 2 NTU in BML surface water treated with 54 mg/L of Ca or 1.1 mg/L of Al. At a concentration of 1.1 mg/L, Al reduced the initial turbidity to a greater extent, and in a shorter time, than 54 mg/L of Ca. Further, resuspended Al-treated FFT particles were 100–700 nm larger in diameter, and thus resettled faster than the resuspended untreated or Ca-treated FFT particles. The final turbidity values 21 days after resuspension of untreated and 1.7 mg/L Al-treated FFT particles in fresh BML surface water were 20.5 NTU and 2.5 NTU, respectively. Thus, Al treatment may be effective in mitigating turbidity in BML through both Al-induced coagulation and self-weight settling of the resuspended Al-treated FFT particles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".