Geotechnical risk management at Teck Coal
Bibliographic record
Abstract
The first standardised Geotechnical Assessment Process for identifying and assessing geotechnical risks at Teck Coal’s open pit mining operations was developed and implemented in 2012. This work was started as a corporate initiative because Teck, as a publicly traded company, desired to demonstrate industry-best practices for managing geotechnical risks and to develop Teck Coal corporate geotechnical standards. Furthermore, corporate geotechnical standards and a consistently high level of geotechnical practice are required as part of the safe and profitable execution of the potential expansions at Teck Coal’s operating sites and the possible development of additional mines. This paper describes the three stage Geotechnical Assessment Process – the application of an assessment tool to scrutinise the geotechnical aspects of mine design, operation and closure, the categorisation and ranking of identified geotechnical risks, and the development of action plans to mitigate the risks. The assessment tool was developed in-house because there were no suitable published or publicly-available procedures. The risk categorisation and ranking procedure was adapted from the existing Teck stage gating process used for major projects. The ranked risks were grouped by common themes, and then used as the basis for developing site-specific ‘Project Initiatives’ that list actionable steps to ensure that each site’s geotechnical systems and processes are aligned with Teck Coal’s emerging standardised approach for identifying and managing the geotechnical risks at existing operations and for potential expansions.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".