Reactivation of an Intraplate Fault by Mine‐Blasting Events: Implications to Regional Seismic Hazard in Western Canada
Bibliographic record
Abstract
Abstract Mining activities are well known for being able to induce local seismicity but have not yet been shown to cause earthquakes over large distances. We analyze a particular group of seismic events recorded from 2014 to 2016 in north‐central British Columbia (BC) that appear to be triggered by the activities at the Mount Milligan Mine. The spatial distribution of the studied events follows a NW‐SE linear trend, with distances up to approximately 100 km from the mining site. To distinguish mining blasts from blasting‐related and natural events, we adopt a multivariate decision tree based on each event's origin time, distance from the mine, and the pseudo‐spectral acceleration ratios of the three‐component waveforms. The calculated dynamic strains from blasts place a distance limit of 20 km for dynamic triggering. However, accounting for the estimated epicentral uncertainty and temporal distribution of the earthquakes' origin times support the existence of blasting‐triggered events at larger distances (up to ∼50 km) from the mine, suggesting that a previously unmapped fault segment is close to critical state and may have been reactivated. The inferred fault segment aligns remarkably well with the southern extent of the Rocky Mountain Trench and may impose a significant hazard to nearby communities if the entire fault segment of about 150 km‐long ruptures.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".