Geotechnical risk management for Victor Mine closure
Bibliographic record
Abstract
The De Beers Canada Victor Diamond Mine is located in the James Bay lowlands of Northern Ontario. This case study presents the evaluation of geotechnical stability and pit lake filling. The work was used to support decisions that informed risk assessments and the closure plan for two key phases: Risk-based monitoring plans were developed along with Trigger Action Response Plans (TARPs) to ensure that closure of the pit proceeds safely and efficiently while satisfying regulatory requirements. Active mining operations in the open pit ceased in mid-2019 and pit filling is underway. The pit required the installation of a major dewatering system, with up to 94,000 m3/day, pumped mostly from dewatering wells. Considerations for closure included the site remoteness, safety, global and local stability, water quality of the pit lake, permitting commitments, and closure regulations in the province of Ontario. A major consideration was the rate of pit filling. Rapid pit lake filling using water from the nearby Attawapiskat River leads to more favourable stability and environmental outcomes. A simple hydrogeological model was used to predict the filling rate and the final pit lake level for a number of potential closure options. This was used to schedule a phased geotechnical monitoring approach to ensure the safety of the operators as the pit walls became increasingly pressurised. A trade-off study has informed the preferred approach for pit lake development. Active pit closure has recently been completed and closure reclamation is ongoing.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".