A comprehensive earthquake catalogue for southwestern Alberta, between 2004 and 2015
Bibliographic record
Abstract
We revisited seismic data recorded from 2004/05 to 2015/01 by regional seismic networks in western Alberta, with the intention of establishing the most comprehensive earthquake catalogue that the data allow. We use a signal-to-noise ratio (SNR) based algorithm to detect earthquake signals, locate the events with a grid-search method, and determine the moment magnitude from time-domain inversion of the observed amplitudes. Our final catalogue contains a total of 306 earthquakes, of which 60 events are missing from routine earthquake monitoring by both Natural Resources Canada (NRCan) and Alberta Geological Survey (AGS). The 306 earthquakes can be roughly grouped into 5 tightly concentrated clusters; several tens of which are, however, broadly distributed in the region. While some of the clusters identified by this study have been studied previously, a potential induced seismicity cluster located at close range to station PER is newly discovered through our analysis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".