An Evaluation of the Applicability of Current Ground-Motion Models to the South and Central American Subduction Zones
Bibliographic record
Abstract
The applicability of existing ground‐motion prediction equations (GMPEs) for subduction‐zone earthquakes is an important issue to address in the assessment of the seismic hazard affecting the Peru–Chile and Central American regions. Few predictive equations exist that are derived from local data, and these do not generally meet the quality criteria required for use in modern seismic hazard analyses. This paper investigates the applicability of a set of global and regional subduction ground‐motion models to the Peru–Chile and Central American subduction zones, distinguishing between interface and intraslab events, in light of recently compiled ground‐motion data from these regions. Strong‐motion recordings and associated metadata compiled by Arango, Strasser, Bommer, Boroschek, et al. (2011) and Arango, Strasser, Bommer, Hernandez, et al. (2011) have been used to assess the performance of the candidate equations following the maximum‐likelihood approach of Scherbaum et al. (2004) and its extension to normalized intraevent and interevent residual distributions developed by Stafford et al. (2008). The results of this study are discussed in terms of the transportability of GMPEs for subduction‐zone environments from one region to another, with a view to providing guidance for developing ground‐motion logic trees for seismic hazard analysis in these regions.
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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 | 0.001 |
| 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 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".