Modeling the Effect of Flocculation and Desiccation on Oil Sands Tailings
Bibliographic record
Abstract
Considerable research has been performed by oil sands mining companies to dewater and manage their fluid fine tailings (FFT) in an effort to meet regulatory and closure requirements. One potential dewatering process includes the addition of flocculants to the FFT and using thickeners to increase the solids content. Additional promising technologies are to surcharge the deposited thickened tailings (TT) or to further thicken the tailings by atmospheric drying. It was found that flocculating and thickening treatments increased the hydraulic conductivity of the fine tailings to some degree, but had no effect on the compressibility and shear strength. Atmospheric drying could enhance the shear strength, but the tailings had to be dried to an unsaturated state, which could be difficult to achieve in the field considering the climate in northern Alberta. Using the geotechnical properties of thickened and desiccated tailings, deposition scenarios for the management of the tailings were modeled. The influence of flocculation and thickening with or without atmospheric drying on a tailings deposit is discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".