THE NGA-SUBDUCTION WEB PORTAL FOR THE DATABASES, PROCESSED TIME SERIES, AND TOOLS
Bibliographic record
Abstract
The NGA-Subduction Project (NGA-Sub) is the latest program in a series of Next Generation Attenuation (NGA) projects directed towards database and ground-motion model (GMM) development for seismic hazard analysis. Whereas prior projects had targeted shallow crustal earthquakes in active tectonic regions (NGA-West1 and NGA-West2) and stable continental regions (NGA-East), NGA-Sub is to address ground motions specifically in subduction zones. Subduction zone earthquakes are a dominant source of seismic hazard in many regions globally, including the Pacific Northwest region of the United States and Canada. The GMMs are based on processed recordings and supporting source, path, and site metadata from seven regions: Alaska, Cascadia, Central America and Mexico, Japan, New Zealand, South America, and Taiwan. The NGA-Sub program has published a variety of products for use in both education, research, and engineering practice. These products consist of: (a) a structured relational database of earthquake-source data, recording-station and site data, and path data, as well as intensity measures such as pseudo spectral accelerations, duration metrics and CAV; (b) a “flatfile”, which is a single table that combines all relevant data and metadata used for ground motion model development; (c) GMMs which provide estimates of the mean and standard deviation of spectral ordinates; (d) coded versions of the GMMs in python, matlab, R, and VB Excel -- the Excel file contains a user-friendly interface for input and output; (e) a dataset of interactive maps for all PSA intensity measures; and (f) a web portal for ground-motion record selection and download. The focus of this paper is on the web portal of the databases and processed time series.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.216 | 0.233 |
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".