Effect of Illite Clay and Divalent Cations on Bitumen Recovery
Bibliographic record
Abstract
The adverse effect of illite clay on bitumen recovery was found to be related to its acidity. The addition of calcium or magnesium ions to the flotation deionized water had a marginal effect on bitumen recovery when measured using a Denver flotation cell. However, the co-addition of illite clay and divalent cations caused a significant reduction in bitumen recovery. The effect was found to be compounded at a lower process temperature and low pH values. Zeta potential distributions of illite suspensions and bitumen emulsions were measured individually and as a mixture to investigate the effect of divalent cations on the interaction between bitumen and illite clay. The presence of 1 mM calcium or magnesium ions in deionized water had a significant effect on the interactions between bitumen and illite clay. Slime coating of illite onto bitumen was not observed in zeta potential distribution measurements performed in alkaline tailings water.
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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) | 0.000 | 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".