New Megathrust Locking Model for the Southern Kurile Subduction Zone Incorporating Viscoelastic Relaxation and Non‐Uniform Compliance of Upper Plate
Bibliographic record
Abstract
Abstract Dense Global Navigation Satellite System (GNSS) observations enable the development of megathrust interseismic locking models for the southern Kurile subduction zone where many great earthquakes have occurred. Inversion of these data assuming uniform elastic Earth has yielded slip deficit rates that are unreasonably high and/or full locking depth that is unreasonably large. Using the finite element method, here we construct a new Kurile locking model that includes interseismic viscoelastic stress relaxation and non‐uniform compliance of the elastic upper plate. Inverting the same geodetic data using the new subduction zone model alleviates the previously seen unreasonable features in inferred megathrust locking state. In the new model, full locking extends to shallower depths than the downdip limit of some large megathrust earthquakes including the 2003 M w 8.0 Tokachi‐oki earthquake, supporting the notion of the shrinking of the locked area before the earthquakes and/or propagation of seismic rupture into creeping areas as previously predicted by friction or dynamic rupture models. By modeling the effects of a few recent M 8 earthquakes, we show that postseismic transients of recent earthquakes, although second‐order, should be addressed in deriving megathrust locking models. The locking state near the trench cannot be resolved by the land‐based GNSS data regardless of the improved model rheology and structure, although independent observations, such as slow earthquakes, may be used to speculate on the near‐trench locking state in various part of the margin in the absence of seafloor geodetic observations.
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 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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".