Earthquake rate, slip rate, and the effective seismic thickness for oceanic transform faults of the Juan de Fuca plate system
Bibliographic record
Abstract
The earthquake rate, average fault slip rate, and the effective seismic thickness have been examined for the Revere—Dellwood—Wilson, Sovanco, Nootka, Blanco and Mendocino transform faults, bordering the Juan de Fuca plate system. Seismicity statistics are related to the rate of slip along a given fault due to earthquakes, using the concept of seismic moment. There are significant sources of uncertainty, including: the incompleteness and limited history of the earthquake catalogue, the variety of magnitude definitions which can only be related empirically, empirical moment–magnitude relations (and the effect of their stochasticity), uncertainty in fault lengths and the effective seismic thickness, the recurrence relation and the determination of maximum magnitude and how the recurrence relation is truncated at maximum magnitude. Nonetheless, this method has been used successfully to provide estimates of deformation in good agreement with those from plate models. An agreement between the deformation rate predicted by seismicity statistics for the fault zones and observed deformation from GPS and other geophysical data is used to show the soundness of the method and parameters used. The least constrained parameter is the effective seismic thickness, thus the effect of a 2, 3, 6.5 and 10 km thick zone is investigated for each fault. The selection of a thin effective seismic layer of about 3 km can consistently explain most of the deformation in the region as being seismically accommodated. The upper mantle is inferred to be aseismic, which is consistent with evidence of its serpentinization beneath these faults. The similarity of the deformation estimates based on seismicity and those from plate models shows a remarkable consistency in these rates over a significant temporal range from tens to millions of years.
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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 | 0.003 |
| 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 | 0.000 | 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".