Dynamics of the Bingham Canyon rock avalanches (Utah, USA) resolved from topographic, seismic, and infrasound data
Bibliographic record
Abstract
Abstract The 2013 Bingham Canyon Mine rock avalanches represent one of the largest cumulative landslide events in recorded U.S. history and provide a unique opportunity to test remote analysis techniques for landslide characterization. Here we combine aerial photogrammetry surveying, topographic reconstruction, numerical runout modeling, and analysis of broadband seismic and infrasound data to extract salient details of the dynamics and evolution of the multiphase landslide event. Our results reveal a cumulative intact rock source volume of 52 Mm 3 , which mobilized in two main rock avalanche phases separated by 1.5 h. We estimate that the first rock avalanche had 1.5–2 times greater volume than the second. Each failure initiated by sliding along a gently dipping (21°), highly persistent basal fault before transitioning to a rock avalanche and spilling into the inner pit. The trajectory and duration of the two rock avalanches were reconstructed using runout modeling and independent force history inversion of intermediate‐period (10–50 s) seismic data. Intermediate‐ and shorter‐period (1–50 s) seismic data were sensitive to intervals of mass redirection and constrained finer details of the individual slide dynamics. Back projecting short‐period (0.2–1 s) seismic energy, we located the two rock avalanches within 2 and 4 km of the mine. Further analysis of infrasound and seismic data revealed that the cumulative event included an additional 11 smaller landslides (volumes ~10 4 –10 5 m 3 ) and that a trailing signal following the second rock avalanche may result from an air‐coupled Rayleigh wave. Our results demonstrate new and refined techniques for detailed remote characterization of the dynamics and evolution of large landslides.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".