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Record W3183070287 · doi:10.1177/87552930211018723

NGA‐East Ground‐Motion Characterization model part I: Summary of products and model development

2021· article· en· W3183070287 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarthquake Spectra · 2021
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsWestern University
FundersElectric Power Research InstituteU.S. Nuclear Regulatory CommissionU.S. Geological SurveyU.S. Department of Energy
KeywordsStandard deviationMoment magnitude scaleRange (aeronautics)Ground motionSeismic hazardHazardGeologySeismologyEngineeringStatisticsMathematicsGeometryAerospace engineering

Abstract

fetched live from OpenAlex

In this article, we present an overview of the research project NGA‐East, Next Generation Attenuation for Central and Eastern North America (CENA), and summarize the key methodology and products. The project was tasked with developing a new ground motion characterization (GMC) model for CENA. The final NGA‐East GMC model includes a set of 17 median ground motion models (GMMs) for peak ground acceleration and velocity (PGA, PGV) and response spectral ordinates for periods ranging from 0.01 to 10 s. The NGA‐East GMMs are applicable to horizontal components of ground motions on very hard rock, for the moment magnitude range of 4.0–8.2, and distances of up to 1500 km. The aleatory standard deviations of GMMs are also provided for site‐specific analysis (single‐station standard deviation) and for general probabilistic seismic hazard analyses (PSHA) applications (ergodic standard deviation). In addition, adjustment factors are provided for source depth and hanging‐wall effects, as well as for hazard computations at sites in the Gulf Coast Region. During the course of the project, several innovative technologies were developed and implemented to increase the transparency and repeatability of the GMC building process. This involved expanding on a set of candidate median GMMs to define and capture an appropriate range of epistemic uncertainty in ground motions. We also developed a new approach for modeling the aleatory variability that was completely independent of the median GMMs. The development made extensive use of the CENA database but also borrowed data from other parts of the world when relevant and led to an integrated suite of models. Through this repeatable process, epistemic uncertainty could be quantified more objectively than before, relying less on expert opinion. The NGA‐East project went through a comprehensive Seismic Senior Hazard Analysis Committee (SSHAC) Level 3 peer review process before its release.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.188
Teacher spread0.174 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it