Effect of suspension conductivity and fines concentration on coarse particle settling in oil sands tailings
Bibliographic record
Abstract
Abstract Sedimentation of coarse particles in mature fine oil sands tailings (OST) was studied by varying the fines concentration and aqueous phase conductivity to determine under which conditions the coarser particles will settle and when they will not. An OST sample was desalinated, separated into finer and coarser fractions, then recombined for settling tests. The isolated finer fraction was predominately phyllosilicate clays (>87 wt%) while the coarser fraction was mostly quartz (<77 wt%). From optical backscattering (OBS) height scan measurements, complete sedimentation of the coarse particles was observed at low conductivity values and fines concentrations, but a sufficient increase in suspension conductivity or fines concentration caused a reduction in coarse particle settlement. Samples with lower fines concentration, 0.5 wt% and 2.4 wt%, exhibited coarse settlement over a wider range of conductivity values; whereas samples with higher fines concentration, 5.9 wt% and 8.2 wt%, exhibited decreased sedimentation even at low suspension conductivity values. At similar conductivity values and fines concentrations, increased sedimentation of pure quartz was observed compared to the coarse OST particles. This difference in settling behaviour was partially attributed to the presence of residual organics on the surface of the OST coarse particles. In addition to typical metallurgical assay methods (x‐ray diffraction and scanning electron microscopy), a synchrotron‐source computed tomography scan of the untreated OST sample was obtained to visualize the distribution of the fine, coarse, and fluid phases within the sample.
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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 | 0.000 | 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) | 0.001 | 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".