Focal mechanism of the induced earthquake of 2015-06-13 (Alberta, Canada), based on waveform inversion
Bibliographic record
Abstract
Understanding the source mechanisms of induced earthquakes is important to distinguish them from natural earthquakes. The main objective of our study consists in finding out which parameters of the source mechanism can be used most effectively to identify the induced earthquakes. A possibility is also being explored whether they can be retrieved from data of a limited number of stations or even just one. We calculate versions of the seismic moment tensor and the corresponding focal mechanisms of the induced event of 2015-06-13 (t0=23:57:53.00 UTC, φ=54.233˚N, λ=-116.627˚E, hs=4 km, ML4.4) near Fox Creek, Alberta, Canada, by inversion of only direct waves recorded at one, two, three and seven stations. The versions turned out to be practically identical, which indicates the advantage of using only direct waves and the very possibility of determining the focal mechanism from the records at the limited number of seismic stations, which may be especially valuable in areas with a sparse seismic network. The versions also turned out to be very similar to the one obtained in [Wang, 2018], which can be considered an additional proof of the reliability of our method. The source time function of the Alberta event had a longer duration (~4 s) than is typical for tectonic earthquakes of similar size. We assume that this very feature may be specific to induced earthquakes and used in combination with others to distinguish them from tectonic earthquakes.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".