Frictional behavior of oceanic transform faults and its influence on earthquake characteristics
Bibliographic record
Abstract
We use a three‐dimensional strike‐slip fault model in the framework of rate and state‐dependent friction to investigate earthquake behavior and scaling relations on oceanic transform faults (OTFs). Gabbro friction data under hydrothermal conditions are mapped onto OTFs using temperatures from (1) a half‐space cooling model, and (2) a thermal model that incorporates a visco‐plastic rheology, non‐Newtonian viscous flow and the effects of shear heating and hydrothermal circulation. Without introducing small‐scale frictional heterogeneities on the fault, our model predicts that an OTF segment can transition between seismic and aseismic slip over many earthquake cycles, consistent with the multimode hypothesis for OTF ruptures. The average seismic coupling coefficient χ is strongly dependent on the ratio of seismogenic zone width W to earthquake nucleation size h *; χ increases by four orders of magnitude as W / h * increases from ∼1 to 2. Specifically, the average χ = 0.15 ± 0.05 derived from global OTF earthquake catalogs can be reached at W / h * ≈ 1.2–1.7. Further, in all simulations the area of the largest earthquake rupture is less than the total seismogenic area and we predict a deficiency of large earthquakes on long transforms, which is also consistent with observations. To match these observations over this narrow range of W / h * requires an increase in the characteristic slip distance d c as the seismogenic zone becomes wider and normal stress is higher on long transforms. Earthquake magnitude and distribution on the Gofar and Romanche transforms are better predicted by simulations using the visco‐plastic model than the half‐space cooling model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".