Geoenvironmental characteristics of Canadian critical metal deposits
Bibliographic record
Abstract
The extraction and processing of critical metals such as niobium (Nb) and the rare earth elements (REEs) has led to environmental degradation in some parts of the world, but there are few published studies of these environmental impacts and related risks to human health. Recent studies in Quebec by the Geological Survey of Canada (GSC) are providing new geoscience knowledge on the geoenvironmental characteristics of Nb and REE deposits. This knowledge should help to reduce the environmental risks of future development of these important resources. In FY 2016-2017, GSC scientists collected samples of mine waste, surface water and groundwater at the abandoned St. Lawrence Columbium mine in Oka, Quebec to better understand the distribution, transport, and fate of metals and radionuclides at this former Nb mine. A gamma-ray spectrometer was used to measure the radiation emitted by decay of naturally occurring uranium (U) and thorium (Th) in the mine waste, and a TerraSpec Halo spectrometer was used to identify specific minerals. Seasonal variations in water quality were measured using instruments installed in groundwater wells, data loggers installed in two flooded pits, and water samplers deployed from a Zodiac in July and October 2016 and from the ice surface in February 2017. Analyses show that mine site surface waters are weakly alkaline and contain low concentrations of fluorine (F), Nb, REEs, U, Th, radium-226, radium-228 and lead-210. The concentrations of these elements are higher in groundwater and in low-oxygen water deeper than 30 m in one of the open pits. This suggests that potentially hazardous elements in the local bedrock and mine waste are relatively immobile in well-oxygenated surface water but may be transported in deeper groundwater. Information from this project will be shared with the Municipality of Oka to help with long-term management of the mine site. The results will also help industry to improve environmental predictions for future Nb- and REE-mines and regulators to develop new environmental guidelines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".