Methanogenic potential of tailings samples from oil sands extraction plants
Bibliographic record
Abstract
Approximately 20% of Canada's oil supply now comes from the extraction of bitumen from the oil sands deposits in northeastern Alberta. The oil sands are strip-mined, and the bitumen is typically separated from sand and clays by an alkaline hot water extraction process. The rapidly expanding oil sands industry has millions of cubic metres of tailings for disposal and large areas of land to reclaim. There are estimates that the consolidation of the mature fine tails (MFT) in the settling ponds will take about 150 years. Some of the settling ponds are now evolving microbially produced methane, a greenhouse gas. To hasten consolidation, gypsum (CaSO4 x 2H2O) is added to MFT, yielding materials called consolidated or composite tailings (CT). Sulfate from the gypsum has the potential to stimulate sulfate-reducing bacteria (SRB) to out-compete methanogens, thereby stopping methanogenesis. This investigation examined three MFT and four CT samples from three oil sands extractions companies. Each was found to contain methanogens and SRB. Serum bottle microcosm studies showed sulfate in the CT samples stopped methane production. However, if the microcosms were amended with readily utilizable electron donors, the sulfate was consumed, and when it reached approximately 20 mg/L, methane production began. Some unamended microcosms were incubated for 372 days, with no methane production detected. This work showed that each MFT and CT sample has the potential to become methanogenic, but in the absence of exogenous electron donors, the added sulfate can inhibit methanogenesis for a long time.
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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 | 0.000 | 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) | 0.001 | 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 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".