Observations on the yielding behaviour of oil sand slurries under vane and slump tests
Bibliographic record
Abstract
Yield stress measurements were carried out on slurries prepared from five different ore samples of varying contents of bitumen and fines in the sand fraction. The rheological measurements were performed using the vane, slump, and relaxation methods, as well as by extrapolation of equilibrium flow curves to zero shear rate. In the case of the vane tests, it was found that the yield stress values agreed better with the results obtained from the other techniques when the yield stresses were calculated using a torque value at the point of departure from linearity on the initial section of experimental torque‐time curves. It was found that the yield stress values of oil sand slurries increased with an increase in bitumen content in the ores. High‐bitumen ores tended to yield within a volume of the slurry extending well beyond the geometry of the vane. In contrast, low‐bitumen ores yielded much closer to the vane edges. As a result, the torque value at the point of departure from linearity on the torque‐time curve was recommended for calculating the yield stress of high‐bitumen ore slurries with the use of the vane technique. On the other hand, the maximum torque value on the torque‐time curve can be used for determining the yield stress of low bitumen ores.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".