Editorial: Seismic microzonation and risk reduction
Bibliographic record
Abstract
Although damaging earthquakes are not very frequent natural events, if compared with other natural 17 risks such as weather-related disasters, the impact of a damaging tremor is much higher in terms of 18 damage to buildings, infrastructure and population and economic losses (direct and indirect). 19 Additionally, earthquakes are the deadliest and most harmful events in developing countries, and the 20 example of the Haiti earthquake (2010) or the Sumatra earthquake (2004) are still in our memories. 21 Understanding seismic risk is the only way to prevent as much as possible damage due to these 22 earthquakes and seismic microzonation is one of the cornerstones to accurately represent the seismic 23 hazard and the related damage. 24The propagation of seismic waves from hard and competent rocks to soft sedimentary layers implies 25 amplification of the amplitude, frequency, and duration of the seismic waves. The so-called site effects 26 represent the description and characterization of the interaction of the seismic wavefield with the near-27 surface structures. Besides, many studies have revealed that topographic features such as slopes, cliffs, 28 hills or canyons are able to alter seismic ground motion significantly. Depending on which part of the 29 topographic feature is considered, seismic ground motion can be either deamplified (i.e. weakened or 30 suppressed) or amplified. The latter has been often observed at hilltops or close to ridges and thereby 31 contributed to greater building damage (Molina et al., 2019). The ground motion, also in combination 32 with the topographic relief and the properties of each geologic unit, may also be responsible for 33 triggering landslides. 34 Knowing the shear wave velocity (VS) structure is important for geophysical data interpretation either 35 to better constrain inversions for P-wave velocity (VP) structures, such as in travel time tomography 36 and full waveform inversions, or as the more relevant parameter in geo-engineering purposes (e.g., 37 ground motion prediction). Passive and active geophysical methods are being widely used in order to 38 This is a provisional file, not the final typeset article characterize the shear-wave velocity structure in 1D, 2D or 3D and even the soil-structure interaction 39 also taking into consideration the nonlinear behaviour of the soils. Furthermore, determining the 40 dominant periods of the ground is relevant in order to relate it to the fundamental period of the buildings 41 so the building resonance may be mapped as a vulnerability factor. 42In this Research Topic, we have collated a set of relevant papers that document some important studies 43 related to the site effects in Bogotá (Colombia), Oslo (Norway) and Vancouver (Canada) and how the 44 road network can be evaluated from the viewpoint of the susceptibility to seismically-induced 45 landslides in Granada (Spain).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".