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Record W2076073049 · doi:10.1785/0120070078

Spatial Correlation of Peak Ground Motions and Response Spectra

2008· article· en· W2076073049 on OpenAlexaff
Katsuichiro Goda, Han Hong

Bibliographic record

VenueBulletin of the Seismological Society of America · 2008
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsCorrelationSpectral lineGeologyGeodesySpatial correlationPhysicsMathematicsStatisticsGeometryAstronomy

Abstract

fetched live from OpenAlex

The intensities of ground motions and structural responses at two sites are correlated. The magnitude of the correlation depends on the distance between the sites and the natural vibration periods of the structures. This study investigates the spatial correlation of the peak ground motions and the pseudospectral acceleration (PSA) responses using the California records and the Chi-Chi records. Because the correlation arises from interevent and intraevent variability, the correlations for individual variability alone and for the combined variability are assessed. The analysis results indicate that the spatial intraevent correlation decreases as the separation distance increases and that the magnitude of the correlation of the PSA responses depends on the considered natural vibration periods. The results also indicate that the spatial intraevent correlation of the PSA responses for the California records decays more rapidly than that for the Chi-Chi records. Based on the analysis results, a simple empirical equation to predict the spatially varying correlation coefficient of the PSA responses, which can be employed in seismic-hazard and seismic-risk assessments, is proposed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.197
Teacher spread0.187 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations302
Published2008
Admission routes1
Has abstractyes

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