Numerical analysis of interseismic, coseismic and post-seismic phases for normal and reverse faulting earthquakes in Italy
Bibliographic record
Abstract
SUMMARY The preparation, initiation and occurrence dynamics of earthquakes in Italy are governed by several frequently unknown physical mechanisms and parameters. Understanding these mechanisms is crucial for developing new techniques and approaches for earthquake monitoring and hazard assessments. Here, we develop a first-order numerical model simulating quasi-static crustal interseismic loading, coseismic brittle episodic dislocation and post-seismic relaxation for extensional and compressional earthquakes in Italy based on a common framework of lithostatic and tectonic forces. Our model includes an upper crust, where the fault is locked, and a deep crust, where the fault experiences steady shear. The results indicate that during the interseismic phase, the contrasting behaviour between the upper locked fault segment and lower creeping fault segment generates a stretched volume at depth in the hangingwall via extensional tectonics while a contracted volume forms via compressional tectonics. The interseismic stress and strain gradients invert at the coseismic stage, with the interseismic dilated volume contracting during the coseismic stage, and vice versa. Moreover, interseismic stress gradients promote coseismic gravitational subsidence of the hangingwall for normal fault earthquakes and elastic uplift for reverse fault earthquakes. Finally, the post-seismic relaxation is characterized by further ground subsidence and uplift for normal and reverse faulting earthquakes, respectively, which is consistent with the faulting style. The fault is the passive feature, with slipping generating the seismic waves, whereas the energy activating the movement is stored mostly in the hangingwall volume. The main source of energy for normal faulting and thrust is provided by the lithostatic load and elastic load, respectively.
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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 | 0.000 | 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 | 0.000 | 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 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".