HVSR MEASUREMENTS OF TWO-DIMENSIONAL SUBSURFACE STRUCTURES – COMPARISONS WITH SEISMIC REFLECTION PROFILES
Bibliographic record
Abstract
Horizontal-to-vertical spectral ratio (HVSR) measurements of ambient seismic noise have gained popularity for seismic microzonation and assessment of earthquake site characteristics such as fundamental frequency (or period). Empirical relationships have been developed to link the fundamental frequency and sediment thickness at sites where a one-dimensional model is a good approximation of the subsurface. This assumption is not always valid, and we present key points when a 1D assumption is out of place. Effects of two-dimensional subsurface structure (non-horizontal layering) have been successfully modelled and can be observed on the orthogonal horizontal spectral ratios in that N-S/V and E-W/V show different peak frequencies and peak amplitudes. We examine both orthogonal horizontal components separately and show that differences between the orthogonal H/V components infer a 2D subsurface. Rotating the horizontal components to maximize/minimize peak amplitudes allows the calculation of azimuthal spectral angles. These preferred angle orientations are shown to be related to the subsurface structure.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".