The dynamic response of coseismic liquefaction-induced ruptures associated with the 2019 <i>M</i> w 5.8 Mirpur, Pakistan, earthquake using HVSR measurements
Bibliographic record
Abstract
Abstract The Mirpur area of Pakistan was severely damaged by extensive coseismic liquefaction following an earthquake of Mw 5.8 on 24 September 2019. Villages within 6 km of the epicenter were adversely affected due to extensive coseismic liquefaction-induced surface and shallow subsurface deformations. The earthquake affected all types of buildings and key infrastructure (e.g., the Upper Jhelum Canal and the main Jhelum–Jatlan road). Field observations and associated effects are presented, including horizontal-to-vertical spectral ratio (HVSR) data sets acquired from three sites to evaluate the site response characteristics of the liquefaction-affected soil profiles. As a result, rupture events strongly influenced spectral features (amplitude and frequency) and site-specific 1D shear-wave velocity profiles at sites S1 and S2. The dynamic behavior of HVSRs across ruptures at sites S1 and S2 corresponds to varied levels of seismic amplification, demonstrating the impact of liquefaction-induced ruptures of seismic origin on the site response that have not been reported previously in the literature. The consistent HVSR pattern of well-established high-frequency peaks at site S3 adjacent to partially damaged to completely collapsed buildings of different types further indicates the susceptibility of potential liquefaction hazard. These results agree with the surface liquefaction signatures in the field, revealed by inverted electrical resistivity tomography models in terms of liquified sand plugs, clay lenses and associated fractures, and increasing trends of radon concentration in the soil with decrease in the distance toward ruptures. Additionally, the successful application of HVSR as a cost-effective and speedy tool attests to the potential of the proposed approach in furnishing complementary information for better assessment of liquefaction hazards in the developing world, where financial constraints are a major issue. This can help with seismic hazard analysis and mitigation in the Mirpur area and may have applications in other seismically active regions of the world.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".