Aseismic transient slip on the Gofar transform fault, East Pacific Rise
Bibliographic record
Abstract
Oceanic transform faults display a unique combination of seismic and aseismic slip behavior, including a large globally averaged seismic deficit, and the local occurrence of repeating magnitude (M) [Formula: see text] earthquakes with abundant foreshocks and seismic swarms, as on the Gofar transform of the East Pacific Rise and the Blanco Ridge in the northeast Pacific Ocean. However, the underlying mechanisms that govern the partitioning between seismic and aseismic slip and their interaction remain unclear. Here we present a numerical modeling study of earthquake sequences and aseismic transient slip on oceanic transform faults. In the model, strong dilatancy strengthening, supported by seismic imaging that indicates enhanced fluid-filled porosity and possible hydrothermal circulation down to the brittle-ductile transition, effectively stabilizes along-strike seismic rupture propagation and results in rupture barriers where aseismic transients arise episodically. The modeled slow slip migrates along the barrier zones at speeds ∼10 to 600 m/h, spatiotemporally correlated with the observed migration of seismic swarms on the Gofar transform. Our model thus suggests the possible prevalence of episodic aseismic transients in M [Formula: see text] rupture barrier zones that host active swarms on oceanic transform faults and provides candidates for future seafloor geodesy experiments to verify the relation between aseismic fault slip, earthquake swarms, and fault zone hydromechanical properties.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".