Structural controls on earthquake rupture revealed by the 2020 Mw 6.0 Jiashi earthquake (Kepingtag belt, SW Tian Shan, China)
Bibliographic record
Abstract
The Kepingtag (Kalpin) fold-and-thrust belt of the southern Chinese Tian Shan is characterized by active shortening and intense seismic activity. Geological cross-sections and seismic reflection profiles suggest thin-skinned, northward-dipping thrust sheets detached in an Upper Cambrian décollement. The January 19 2020 Mw 6.0 Jiashi earthquake provides an opportunity to investigate how coseismic deformation is accommodated in this structural setting. Coseismic surface deformation resolved with Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) is centered on the back limb of the frontal Kepingtag anticline. Elastic dislocation modelling suggests that the causative fault is located at ~7 km depth and dips ~7° northward, consistent with the inferred position of the décollement. The narrow slip pattern (length ~37 km but width only ~9 km) implies that there is a strong structural or lithological control on the rupture extent, with up-dip slip propagation possibly halted by an abrupt change in dip angle where the Kepingtag thrust is inferred to branch off the décollement. A depth discrepancy between mainshock slip constrained by InSAR and teleseismic waveform modelling (~7 km) and well-relocated aftershocks (~10-20 km) may imply that sediments above the décollement are velocity strengthening. We also relocate 148 regional events from 1977 to 2020 to characterize the broader distribution of seismicity across the Kepingtag belt. The calibrated hypocenters combined with previous teleseismic waveform models show that thrust and reverse faulting earthquakes cluster at relatively shallow depths of ~7-15 km but include abundant out-of-sequence events both north and south of the frontal Kepingtag fault.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".