Assessment of critical mineral extraction from brines at Mount Meager, Southwestern BC, Canada
Bibliographic record
Abstract
intensive mining methods. This paper evaluates the potential of geothermal brines as a sustainable alternative for mineral extraction after geothermal energy production. A detailed case study of a Canadian geothermal field provides insight into the potential economic advantages of mineral extraction from brines. Water chemistry data from the Mount Meager geothermal field, which has one of the highest geothermal potentials in Canada, demonstrates that the fluids are rich in dissolved minerals and metals. Using reservoir physical information, Monte Carlo simulations, and appropriate probability distributions, our study addresses uncertainties in volumetric resource calculations. Taking into consideration flow pathways through the rock matrix, and available technologies with rates of mineral recovery up to 90%, results show promising reserves for minerals such as lithium, magnesium, and silica. The findings highlight the dual benefits of geothermal energy in Canada providing both a green energy source and facilitating critical mineral production. This dual utility can generate additional revenue fostering the development of geothermal fields, even those that are not viable for energy generation on their own, supporting Canada's transition to a low-carbon economy.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".