The Iquique earthquake sequence of April 2014: Bayesian modeling accounting for prediction uncertainty
Bibliographic record
Abstract
Abstract The subduction zone in northern Chile is a well‐identified seismic gap that last ruptured in 1877. On 1 April 2014, this region was struck by a large earthquake following a two week long series of foreshocks. This study combines a wide range of observations, including geodetic, tsunami, and seismic data, to produce a reliable kinematic slip model of the M w =8.1 main shock and a static slip model of the M w =7.7 aftershock. We use a novel Bayesian modeling approach that accounts for uncertainty in the Green's functions, both static and dynamic, while avoiding nonphysical regularization. The results reveal a sharp slip zone, more compact than previously thought, located downdip of the foreshock sequence and updip of high‐frequency sources inferred by back‐projection analysis. Both the main shock and the M w =7.7 aftershock did not rupture to the trench and left most of the seismic gap unbroken, leaving the possibility of a future large earthquake in the region.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".