Ore types impact on flocculation and the treatment strategies for different types of oil sand tailings
Bibliographic record
Abstract
Alberta oil sand ore is generically classified by depositional environment: fluvial, estuarine, transition and marine. It is well known that the ores associated with the four types of depositional environments behave differently in the bitumen extraction process. Also, the different ore types have a significant impact on flocculation and thickening of the oil sand tailings. This paper will discuss the fundamental research on the ore type effect on flocculation and the related treatment strategies for different types of oil sand tailings. These treatments include the uses of a single flocculant, a single coagulant and a combination of flocculant and coagulant injected in different sequences of the process. It was found that the sequences of flocculant and coagulant injections have profound impact on flocculation performance. The test data are discussed in association with the flocculation principles. Based on these findings, the engineering control strategies to handle various types of feeds of oil sand tailings to a thickener are also proposed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".