Potential climate change effects on the geochemical stability of waste and mobility of elements in receiving environments for Canadian metal mines south of 60°N
Bibliographic record
Abstract
Increased temperatures and changing amounts of precipitation may alter environments, increasing the challenges faced by mines. This is a paper on topics relevant to metal mine biogeochemical environments, related waste management, element transport, and environment health south of 60° latitude. Mine waste can contain elements of interest (EOI) that may have adverse environmental and biological effects at concentrations that are higher than in undisturbed sites. Elevated concentrations of EOIs are transported by water as solutes and particles. Wind erosion also transports particles, and establishing its contribution and effects is challenging. Dispersal of EOI can be controlled at the source using water covers, geomembranes, geosynthetic clay liners, and covers with capillary barrier effects. Drainage that can be produced over a wide range of pH must be treated to meet environmental requirements. Water treatment can produce sludge that must be stored or processed. The success of these mitigation measures can be observed in the biological health of organisms at the site and vicinity. Processes responsible for EOI dissolution and transport, waste control and water management systems, and the stress experienced by biota near mines are all subject to climate change effects. Understanding and adapting to challenges from a rapidly changing environment will require cooperation between industry, government, mining communities, and scientists. Ideally, adaptation measures should correspond to temperature and precipitation projections, but this information is not always available at the relevant geographic scale. To anticipate emerging risks, it may be necessary to explore a variety of scenarios at lab and field scales, and to implement robust and flexible management techniques.
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 | 0.001 | 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".