Implementing a stability monitoring system at a legacy mine site—case study
Bibliographic record
Abstract
Canada has a rich history of mining that has played a significant role in shaping Canada's economy and development. Mining has also left a lasting legacy in the form of closed or abandoned mines. These mine sites often pose safety risks, specifically related to the stability of historical open pit and underground workings— their closure and remediation present significant challenges. This paper discusses a legacy mine site case study focusing on the implementation of a suitable rock mass stability monitoring system. The legacy mine site is located within the town boundaries of a community in northern Canada. The site includes an interconnected open pit and underground workings where some of the mine workings were backfilled. Based on available information, the mine was closed after a failure occurred at depth and some backfill material was lost to a deeper section of the mine. A pond currently exists where the open pit was located. This paper includes a detailed discussion of the existing instrumentation and the implementation of a more comprehensive stability monitoring strategy. The stability in this case is of particular importance, as the site is close to community infrastructure, and consequently, community residents. This paper addresses the benefits of the selected monitoring system and each system component, and includes the challenges resulting from the geographical location, rock mass conditions, and maintenance due to the remoteness of the site. There were no local employees available to address the monitoring system health. The site has not experienced any documented instability since the mine had closed, based on almost three decades of shallow monitoring and site observations. The installation of monitoring systems is usually, targeted at monitoring movement. However, for this site, instability and ground movement were not expected, leading to monitoring focusing on system health and the detection of potential movement. The lack of employees on site also made the health and functionality of the monitoring system critical as there was a desire to prevent frequent system maintenance and troubleshooting.
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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".