Updated Compilation of VS30 Data for the United States
Bibliographic record
Abstract
VS30, the time-averaged shear-wave velocity (VS) to a depth of 30 meters, is a key index adopted by the earthquake engineering community to account for seismic site conditions. VS30 is typically based on geophysical measurements of VS derived from invasive and noninvasive techniques at sites of interest. Owing to cost considerations, as well as logistical and environmental concerns, VS30 data are sparse or not readily available for most areas. Where data are available, VS30 values are often assembled in assorted formats that are accessible from disparate and (or) impermanent Websites. To help remedy this situation, we compiled VS30 measurements obtained by studies funded by the U.S. Geological Survey (USGS) and other governmental agencies. Thus far, we have compiled VS30 values for 4,369 sites in the United States, along with metadata for each measurement from government-sponsored reports, online databases, and scientific and engineering journals. Most of the data in our VS30 compilation originated from publications directly reporting the work of field investigators. A subset consisting of 20 percent of VS30 values was previously compiled by the USGS and other research institutions. VS30 originating from these earlier compilations were crosschecked against published reports when clarification was needed. Both downhole and surface-based VS30 estimates are represented in our VS30 compilation. Most of the VS30 data are for sites in the western contiguous United States (3,128 sites); 682 VS30 values are for sites in the Central United States; 267 VS30 values are for sites in the Eastern United States and Puerto Rico; 15 VS30 values are for sites in Alaska; 30 VS30 values are for sites in Hawaii. The remaining 247 sites are in the vicinity of Vancouver, Canada.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.016 |
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".