A case study of dynamic triggering in the Kiskatinaw area of the Montney Formation, British Columbia
Bibliographic record
Abstract
In this study I investigate the potential occurrence of remote dynamic triggering in the Kiskatinaw area of British Columbia, Canada, over a 30-month time interval following the installation of the McGill seismic network.I use visual waveform analysis, as well as a multi-station matched filter catalogue enhancement method, to detect any remotely triggered earthquakes.Potentially-triggering mainshocks are required to surpass a measured peak ground velocity of 100 µm/s, surface wave magnitude ≥ 6, and have depths ≤ 100 km.The visual analysis method reveals triggered events buried within the teleseismic surface waves of two mainshocks, as well as events up to 4 hours after a mainshock's first arrival.Following the catalogue enhancement for 5 days before and after each candidate mainshock, I use a combination of the P , γ, β, and Z statistical tests to confirm that seismicity rate increases are significant enough to indicate triggering.I find multiple mainshocks with statistically-significant triggering, each of which with depths < 35 km and measured peak dynamic triggering stresses from 5-16 kPa.I also observe transient stresses responsible for directly triggering events down to 0.05 kPa, implying that the responsive faults are critically-stressed, and have a triggering threshold lower than previously observed in this region.Two of the triggering mainshocks are not associated with injection activity in the 10-day catalogue enhancement periods, indicating that pore pressures may have remained high in the region for days or weeks after injection has ceased.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".