Directivity analysis of the 2017 December Kerman earthquakes in Eastern Iran
Bibliographic record
Abstract
Abstract Using an empirical Green’s function (EGF) approach and data from local to regional distances we analyzed rupture propagation directivity in the three mainshocks (ML 6.0–6.1) and in six of the largest aftershocks (ML 5.0 – 5.5) of the 2017 Kerman, Iran, seismic sequence. The EGF procedure was based on data from smaller events (ML 4.0 – 4.8). Deconvolution was applied separately to P and S phases. Using the P-wave data, we calculated relative source-time functions and examined azimuthal variations in rupture duration. In the S-wave analysis, we investigated along strike rupture directivity of the mainshocks and the largest aftershocks by evaluating azimuthal variation of the amplitude spectra. Two of the mainshocks and four of the aftershocks clearly showed rupture propagation from the south-east toward the north-west. The third mainshock and one of the aftershocks suggested almost bilateral rupture propagation, and one aftershock showed rupture directivity to the southeast. It seems that the rupture propagation direction in the area is generally to the north-west and the events which have different propagation directions are located within the NW and SE ends of the faulting area. We suggest that the general rupture propagation direction in the area is steered by regional tectonic stress field regarding the faulting orientations which have been affected by stress redistribution around a restraining bend.
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".