THE ECONOMIC CHALLENGES OF DEWATERING AT THE VICTOR DIAMOND MINE IN NORTHERN
Bibliographic record
Abstract
The challenges of mining economically have never been greater than under current global financial conditions. The costs and efficiency of dewatering are particularly important at De Beers Canada’s Victor diamond mine in northern Ontario where: 1) the bottom of the water-bearing carbonate country rocks is near the bottom of the planned pit, limiting the available drawdown in perimeter wells; 2) the majority of inflow to the wells comes from a very limited number of discrete zones in the carbonate rocks, resulting in low hydraulic efficiencies of the wells; 3) line power to the mine is limited, mandating efficient pumping over a wide range of yields and lifts; and 4) the relatively isolated northern setting and extreme cold winter temperatures (which can reach-40 to-60 deg C) present logistical issues (e.g., insulation of wellheads and pipelines, and having to truck in heavy materials over an ice road during a relatively short period of time). The hydrogeology of the Victor mine area was characterised over three relatively short winter field seasons using packer tests, pumping tests, step-drawdown tests, and downhole logging (particularly production or “spinner ” logs) to define the lateral and vertical variation in the hydraulic conductivity of the carbonate aquifer. Based on analysis of the
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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 | 0.000 | 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".