Deep long-period earthquakes near Mount Meager, British Columbia
Bibliographic record
Abstract
Deep long-period earthquakes (DLPs) are a class of seismicity that has been documented in volcanic fields worldwide and are thought to be related to the motion of fluids (magmas and volatiles) associated with volcanic processes. We applied an automatic event detection algorithm to stations of the Canadian National Seismograph Network in southwestern British Columbia and documented the first DLPs observed within the Garibaldi Volcanic Belt. A total of 42 events satisfying the spectral criteria of DLPs were detected at station PMB between 1993 and 1998, of which 26 events were located using three-component polarization analysis and 1-D ray tracing. An additional six events were identified and located from station MGMB between 2016 and 2019. The events are small ( ML ∼ 0) and the majority of the epicenters are clustered at ∼45 km ENE of Mount Meager, the site of Canada’s most recent large eruption at 2.4 ka. They lie in closer proximity and may be related to Quaternary volcanism associated with the Bridge River Cones.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".