An Assessment of Rockfall Triggers and Seasonal Weather Trends Through An Examination of Railway Slope Management Procedures
Bibliographic record
Abstract
Rockfalls are one of the many geohazards that impact railways across Canada with the potential to cause operational delays, damage to infrastructure and the environment, and injury or loss of life. To minimize the risk associated with these scenarios, railways rely on slope management systems that standardize assessment procedures, slope inventories, and rockfall recording methods to help understand the spatial and temporal nature of rockfall occurrences and guide mitigation decisions. This study examines the slope management systems of Canadian Pacific Rail and the Iron Ore Company of Canada and aims to provide new insight into the triggering of rockfall events through an assessment of seasonal weather trends along track segments from each of the railways. The CPR Engineering and Management of Rock Slopes directive was designed to support the prioritization of maintenance work while the IOC Geohazard Management System was designed to conduct a life-loss assessment using a risk-based framework. This review highlighted that although intended for different goals, both systems benefitted from personnel training and participation and underlined the importance of developing standards and records to help learn about and effectively manage rockfalls. The relationship between monthly rockfall distribution, precipitation, and freeze-thaw trends - the two primary rockfall triggers - were assessed using the von Mises modelling methodology outlined in Macciotta et al., (2017) for the HeBa (CPR) and Gagnon Sud (IOC / QNS&L) segments. The HeBa analysis was conducted using a 26-year rockfall and weather record (209 events) and resulted in a 0.92 correlation to the rockfall records, while the Gagnon Sud analysis used an 8-year rockfall record (76 events) and 5-year weather record and resulted in a 0.86 correlation. Modelling from both analyses pointed to precipitation as the primary cause for rockfall events in the summer and fall, while spring events were mostly triggered by freeze-thaw action. Comparisons to previous work in western Canada showed that the more moderate climates tended to experience peak rockfall activity in the fall or winter, depending on the degree of cooling, while HeBa and Gagnon Sud in eastern Canada experienced peak rockfall activity in the spring after a deep winter thaw.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".