Bibliographic record
Abstract
Fine fluid tailings (FFT) are a by-product created during the extraction of bitumen from oil sands mining operations. Over 975 million m3 of FFT are currently being stored in tailings ponds in the Athabasca oil sands region (AOSR) of Alberta, Canada. These tailings cause industrial and environmental concerns due to storage and management issues, and potential hazard to the surrounding environment. A potential solution for managing these tailings ponds is to dewater them through technologies such as centrifugation and use the dewatered FFT cake as a subsoil material in reclamation. The FFT would need to be capped with suitable soil and depth in order to support plant growth and meet reclamation requirements. The optimal minimal capping material and depth are not well studied. In the first study (Chapter 2), a 16-week greenhouse study was conducted to assess whether FFT cake and caps of various mixes and depths (0, 5, 10 and 20 cm depth) of forest floor mineral mix (FFMM) and peat mineral mix (PMM) would support plant growth of trembling aspen (Populus tremuloides – native broadleaf tree) and beaked willow (Salix bebbiana – native broadleaf shrub). S. bebbiana had a greater survival rate (100%) when grown directly in FFT cake compared to P. tremuloides (16.7%). The same S. bebbiana seedlings had 10 times higher foliar concentrations of Al, Cr and Ti compared to any other treatments. Plants grown directly in FFT cake were negatively impacted by high water content and low nitrate supply rates. S. bebbiana can tolerate and survive in these high metal, saturated soil, and low NO3- conditions while P. tremuloides could not. However, adding any soil cap significantly increased aboveground biomass for both species. The capping material that best supported plant growth was a mixture of FFMM and PMM, although differences among soil types were not large. The 5 cm capping depths for PMM and FFMM in P. tremuloides had significantly reduced aboveground biomass, likely caused by the FFT cake’s poor draining which resulted in saturated soils. Results from this study show that capping FFT cake at a minimum depth of 10 cm substantially improves woody plant growth, and S. bebbiana and P. tremuloides are potentially suitable species for tailings reclamation. In the second study (Chapter 3), biochar was added to one of the capping treatments (1:1 ratio of PMM and FFMM at 10 cm depth over FFT cake) to determine if it had any positive effect on plant growth. The results found that there were no differences between the biochar treatment and the non-biochar treatments.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".