Contemporaneous Thick- and Thin-Skinned Seismotectonics in the External Zagros: The Case of the 2021 Fin Doublet, Iran
Bibliographic record
Abstract
In this work, we propose a geodetic model for the seismic sequence, with doublet earthquakes, that occurred in Bandar Abbas, Iran, in November 2021. A dataset of Sentinel-1 images, processed using the InSAR (Interferometric Synthetic Aperture Radar) technique, was employed to identify the surface deformation caused by the major events of the sequence and to constrain their geometry and kinematics using seismological constraints. A Coulomb stress transfer analysis was also applied to investigate the sequence’s structural evolution in space and time. A linear inversion of the InSAR data provided a non-uniform distribution of slip over the fault planes. We also performed an accurate relocation of foreshocks and aftershocks recorded by locally established seismographs, thereby allowing us to determine the compressional tectonic stress regime affecting the crustal volume. Despite the very short time span of the sequence, our results clearly suggest that distinct blind structures that were previously unknown or only suspected were the causative faults. The first Mw 6.0 earthquake occurred on an NNE-dipping, intermediate-angle, reverse-oblique plane, while the Mw 6.4 earthquake occurred on almost horizontal or very low-angle (SSE-dipping) reverse segments with top-to-the-south kinematics. The former, which cut through and displaced the Pan-African pre-Palaeozoic basement, indicates a thick-skinned tectonic style, while the latter rupture(s), which occurred within the Palaeozoic–Cenozoic sedimentary succession and likely exploited the stratigraphic mechanical discontinuities, clearly depicts a thin-skinned style.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".