Impact of flocculation-based dewatering on the shear strength of oil sands fine tailings
Bibliographic record
Abstract
The oil sands in northern Alberta have been mined to produce bitumen over the past five decades. Since the 1980s, technical advances have been made in mining, material handling, and bitumen extraction. However, acquiring practical methods to control and reduce the fluid fine tailings build-up has been an ongoing challenge. Recent regulatory changes have driven the industry to review current tailings-management techniques and investigate numerous alternative technologies and processes to manage and reclaim fine tailings. Many of these fine tailings–management techniques involve some form of polymer or chemical addition to promote dewatering and strength gain to meet the regulatory requirements. Based on the reported data, the chemically amended fine tailings deposits have the characteristics of sensitive, metastable deposits, necessitating additional mitigative measures by oil sands operators beyond the regulatory requirements. This paper explores the geotechnical aspects of meeting regulatory strength performance criteria by employing flocculation-based dewatering of fluid fine tailings.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".