Fault Slip Behaviors Modulated by Locally Increased Fluid Pressure: Earthquake Nucleation and Slow Slip Events
Bibliographic record
Abstract
Abstract Huge earthquakes are frequently preceded by slow slip events (SSEs) that are speculated as the precursor to regular earthquakes (REs). However, the way in which earthquakes initiate, as well as the interactions between SSEs and REs remain poorly understood, adding more mysteries to the initiation of earthquakes. Here, we perform systematic numerical simulations to explore the relationships between SSEs and REs on faults including locally increased fluid pressure. We identify four types of fault slip behaviors distinguished by SSE and earthquake initiation mode. The observed interactions between SSEs and REs share similar features with those reported for natural earthquakes. Our results show that the occurrence of SSEs may temporarily hasten fault decoupling, leading to the clock advance of mainshocks. Furthermore, the interactions between SSEs and REs are more complicated than previously thought. On the one hand, since SSEs with extremely high peak slip rates tend to directly transform into huge earthquakes, the possibility of huge earthquakes may increase when SSEs happen. On the other hand, there is no threshold in peak slip rate for SSEs to trigger the nucleation of REs. Therefore, it is difficult to distinguish the SSEs that could trigger a huge earthquake from regular ones only with the knowledge of the peak slip rate. We also verify that the spatial extent of SSEs is related to the occurrence of earthquakes to some extent. These findings may have major implications for understanding the interactions between SSEs and REs, and the mechanism of earthquake initiation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".