Prospective Fault Displacement Hazard Assessment for Leech River Valley Fault Using Stochastic Source Modeling and Okada Fault Displacement Equations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, an alternative method for conducting probabilistic fault displacement hazard analysis is developed based on stochastic source modeling and analytical formulae for evaluating the elastic dislocation due to an earthquake rupture. It characterizes the uncertainty of fault-rupture occurrence in terms of its position, geometry, and slip distribution and adopts so-called Okada equations for the calculation of fault displacement on the ground surface. The method is compatible with fault-source-based probabilistic seismic hazard analysis and can be implemented via Monte Carlo simulations. The new method is useful for evaluating the differential displacements caused by the fault rupture at multiple locations simultaneously. The proposed method is applied to the Leech River Valley Fault located in the vicinity of Victoria, British Columbia, Canada. Site-specific fault displacement and differential fault displacement hazard curves are assessed for multiple sites within the fault-rupture zone. The hazard results indicate that relatively large displacements (∼0.5 m vertical uplift) can be expected at low probability levels of 10−4. For critical infrastructures, such as bridges and pipelines, quantifying the uncertainty of fault displacement hazard is essential to manage potential damage and loss effectively.
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.
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 | 0.000 | 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 | 0.001 | 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) | 0.000 | 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 it