Simulation of seismic hazard parameters and earthquakes source mechanisms along the Red Sea rift, western Saudi Arabia
Bibliographic record
Abstract
Abstract Well-recorded earthquakes located along the rift axis of the Red Sea, western Saudi Arabia, were investigated. These events are among the most significant recorded between 1997 and 2024 in this seismic zone. The moment tensor inversion, using full waveform data, was applied to determine the rifting mechanism and parameters of the investigated earthquakes. The optimum double-couple mechanism for investigated earthquakes revealed normal faulting with minor strike slip movement along the red sea spreading axis. The most recent earthquakes were felt in nearby cities, prompting a study to understand the fault mechanisms and assess the impact of strong ground motion parameters on western Saudi Arabian cities, which have rapidly developed along the Red Sea’s active rifting system. The stochastic simulation method, based on the site spectral model, was used to estimate the effects and strong ground motion parameters of the most recent and significant earthquakes in the western cities of Saudi Arabia: one on June 16, 2020 ( M L {M}_{{\rm{L}}} = 5.5), and another on April 14, 2023 ( M L {M}_{{\rm{L}}} = 4.5). The results suggest that Al-Muwaileh and Duba cities experienced peak ground accelerations of 9.113 and 8.673 cm/s 2 from the June 16, 2020, earthquake and 2.347 and 1.707 cm/s² from the April 14, 2023, earthquake, respectively. The pseudo-seismic spectral acceleration values were 2.282 × 10 1 and 2.379 × 10 1 cm/s 2 in Duba and Al-Muwaileh, respectively, for the June 16, 2020, earthquake and 4.837 and 6.752 cm/s 2 for the April 14, 2023, earthquake.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".