Wettability of fine solids extracted from bitumen froth
Bibliographic record
Abstract
Oil sands deposits in northern Alberta contain more hydrocarbons than all OPEC reserves combined. The amount recoverable using the existing technology is slightly larger than the total oil reserves of Saudi Arabia. Today, the total production of oil from oil sands amounts to over 20% of Canadian oil consumption, threequarters of which is from open pit mining; the remainder comes from in situ recovery. Clark’s hot water extraction process and its modifications have been used to separate bitumen from the oil sand ore. In this process, the mined oil sand is mixed with hot water and the digested slurry is fed into large gravity separation vessels, where bitumen is recovered as a froth product in a process similar to flotation. The froth produced as such typically contains ca. 60% bitumen, 30% water, and 10% solids. The froth is cleaned by adding a diluent (an organic liquid mixture, such as naphtha) to provide a density difference between the water and hydrocarbon phases and to reduce the viscosity of the froth. The diluted bitumen is then fed through a two-stage centrifuge (at ca. 250 x and 2500 x g, respectively) to remove coarse particles in the first stage by scroll machines and the remaining fine solids and finely dispersed water droplets in the second stage by disc centrifuges. (Inclined plate settlers and/or third-stage centrifuges are also used in commercial operations.) Collectively called froth treatment, this process produces a product still containing ~ 2% water and 0.5% solids.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".