Seismic-Wave Attenuation Determined from Tectonic Tremor in Multiple Subduction Zones
Bibliographic record
Abstract
Abstract Tectonic tremor provides a new source of observations that can be used to constrain the seismic attenuation parameter for ground‐motion prediction and hazard mapping. Traditionally, recorded earthquakes of magnitude ∼3–8 are used to develop ground‐motion prediction equations; however, typical earthquake records may be sparse in areas of high hazard. In this study, we constrain the distance decay of seismic waves using measurements of the amplitude decay of tectonic tremor, which is plentiful in some regions. Tectonic tremor occurs in the frequency band of interest for ground‐motion prediction (i.e., ∼2–8 Hz) and is located on the subducting plate interface, at the lower boundary of where future large earthquakes are expected. We empirically fit the distance decay of peak ground velocity from tremor to determine the attenuation parameter in four subduction zones: Nankai, Japan; Cascadia, United States–Canada; Jalisco, Mexico; and southern Chile. With the large amount of data available from tremor, we show that in the upper plate, the lower crust is less attenuating than the upper crust. We apply the same analysis to intraslab events in Nankai and show the possibility that waves traveling from deeper intraslab events experience more attenuation than those from the shallower tremor due to ray paths that pass through the subducting and highly attenuating oceanic crust. This suggests that high pore‐fluid pressure is present in the tremor source region. These differences imply that the attenuation parameter determined from intraslab earthquakes may underestimate ground motion for future large earthquakes on the plate interface.
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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 | 0.000 | 0.000 |
| 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".