Estimation of Bitumen and Solids Content in Fine Tailings Using Low-Field NMR Technique
Bibliographic record
Abstract
Summary The oil sands mining and extraction processes in Canada produce large volumes of tailings that are a mixture of mainly water, clay, sand, chemicals and bitumen. This mixture is transported to tailings ponds, where gravity segregation occurs. During this process, a stable suspension called mature fine tailings (MFT) is formed, which requires many years to fully consolidate. Therefore, land reclamation and water recirculation become significant environmental issues. For this reason, it is important to understand the tailings' content and their settling properties. This study uses the low-field nuclear magnetic resonance (NMR) technique to estimate the water, bitumen and solids composition of synthetic and real tailings samples through a bimodal compositional detection method under ambient conditions. NMR measurements were conducted in 15 minutes, which is a relatively fast measurement allowing for rapid monitoring of tailings compositions. The results show that the NMR technique can be a potential on-site fast measurement of composition and settling characteristics of tailings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".