Numerical Modeling of Dynamically Triggered Shallow Slow Slip Events in New Zealand by the 2016 <i>M</i><sub><i>w</i></sub> 7.8 Kaikoura Earthquake
Bibliographic record
Abstract
Abstract The 2016 Mw 7.8 Kaikoura earthquake triggered widespread slow slip events (SSEs) in the northern Hikurangi subduction zone, providing a unique opportunity to study the mechanism of dynamic triggering of SSEs. Here we simulate SSEs near Gisborne, New Zealand, in the framework of rate‐and‐state friction. Low effective normal stress (~0.4 MPa) on the shallow subduction interface is needed to reproduce the observed repeating, spontaneous SSEs. Dynamic stress perturbations from the Kaikoura mainshock are adequate to trigger SSEs with characteristics similar to observation. SSE propensity to dynamic triggering mainly depends on the timing of perturbation with respect to the SSE cycle and the maximum Coulomb stress change. Once the perturbation amplitude exceeds an initial threshold, prolonged stress perturbations tend to decrease the triggering threshold hence promote dynamic triggering of SSEs. Therefore, shallow SSEs are more likely to be dynamically triggered than their deep counterparts because of enhanced stress perturbation (magnitude and duration) from the sedimentary wedge.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".