The impact of reclamation cover depth on the performance of reclaimed shale overburden at an oil sands mine in Northern Alberta, Canada
Bibliographic record
Abstract
Abstract Multilayer covers are widely accepted reclamation designs in the oil sands region of northern Alberta, Canada, with an ultimate goal of revegetating to species characteristic of predisturbance native plant communities. To determine the optimal depth of reclamation material required to reclaim overburden shale from an oil sands mine, an evaluation was made of the long‐term performance of six reclamation soil cover depths all placed over overburden. The measured soil water contents from different cover thicknesses at South Bison Hills located at the Syncrude Mine site north of Fort McMurray, Alberta, were used to calibrate and validate a dual‐porosity model in HYDRUS‐1D. The calibrated and validated model was then used to evaluate the influence of cover thickness and climatic variability on plant available water for forest growth. The frequency distributions of actual transpiration (Tr) for six cover treatments with a range of leaf area index (LAI) cases were developed. These Tr frequency distributions were then modified by coupling Tr and LAI. The modified frequency distributions for annual Tr for the six simulated cover thickness highlight the strong nonlinearity between the distributions of Tr over a long‐term (60 years) climate cycle in that incremental increases in cover thickness do not produce proportional increases in Tr. The results indicated that, once the cover thickness exceeds 100 cm, there is little incremental increase in the median value of Tr over the 60‐year climate cycle. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".