Sustainable development of open pit mines: creating beneficial end uses for pit lakes
Bibliographic record
Abstract
Water quality of pit lakes is one of the most critical environmental issues facing the global mining industry. As ore grades decrease and operators strive to improve efficiency, the number of active pit mines will continue to outpace their underground counterparts in the years ahead. How will these water resources be protected for future generations while the mining industry continues to meet society's growing demands for raw materials? The key to solving this dilemma is accurately predicting the water quality in advance of open pit mining. That's the purpose of Mine Pit Lakes. The third in a series of six handbooks by the Acid Drainage Technology Initiative, Metal Mining Sector (ADTI-MMS), this volume includes the latest thinking from dozens of internationally respected experts from Canada, Germany, Australia, and the United States. You'll learn both the theory and science of predicting pit lake water quality and get insights into the best practices of pit lake management. This book is an indispensable resource for mining professionals and environmental regulators who are considering new open pit mines or are developing monitoring programs or closure strategies for existing ones.
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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 | 0.001 | 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".