Integration of geosynthetics in reclaiming an oil sands tailings pond
Bibliographic record
Abstract
Global mining operations produce significant amounts of soil waste referred to as tailings. In oil sands mining, a portion of the deposited tailings is extremely soft and is primarily in a fluid state with solid contents (by weight) ranging between 30% and 40%. As part of reclaiming its Pond 5 oil sands tailings pond, Suncor constructed an engineered “floating” cover on top of the soft tailings deposits between 2010 and 2017 over an area spanning approximately 200 hectares to provide trafficability for limited construction equipment. This initial cover consisted of two layers of geosynthetics overlain by 2 m of petroleum coke. After construction of the initial cover, Vertical Strip Drains (VSDs) were installed through the majority of the capped area to enhance the consolidation rate of the underlying soft tailings. Additional coke has been placed on top of the initial coke cover to a total thickness of 4 m to 6 m. Previous publications have discussed the cover design, installation details of the geosynthetics, installation and performance of the VSDs, and performance of the cover. This paper presents the geosynthetics design, inspection of the geosynthetics post cover construction, and an update on the performance of the coke cover.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".