Impact of fine solids on mined Athabasca oil sands extraction I. Floatability of fine solids
Bibliographic record
Abstract
Abstract Understanding the mechanisms by which fine solids are recovered to bitumen froth during oil sands extraction plays a critical role in minimizing the detrimental effect of fines on bitumen recovery and froth quality. A simple method was presented in this study to distinguish fine solids recovery by water entrainment from that by true flotation. Dispersed air flotation was carried out, using a 1‐L Denver flotation cell, to evaluate flotation behaviours of different sizes and types of fine solids (< 5 μm up to < 40 μm silica, < 5 μm kaolinite clays, and < 44 μm fine solids extracted from oil sands). The results show that dispersed individual fine solids in oil sands slurries could be recovered to the froth by mechanical entrainment, and by true flotation. While the recovery of hydrophilic fine solids decreased with increasing particle sizes by water entrainment, the recovery of hydrophobized fine solids, due to dodecylamine adsorption, increased with increasing particle sizes by true flotation. Fine solids extracted from oil sands behaved differently from pure silica or clays: they adsorbed amine slowly, and responded to flotation slowly. The exact reasons remain to be explored.
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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 | 0.001 | 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".