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Record W4387270580 · doi:10.36487/acg_repo/2315_098

Implementing a stability monitoring system at a legacy mine site—case study

2023· article· en· W4387270580 on OpenAlexaboutno aff
Olga Gibbons, A Hartzenberg, Adrienne Joaquim, Tim Coleman

Bibliographic record

VenueMine closure · 2023
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.688

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.039
GPT teacher head0.269
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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