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Record W4236439260 · doi:10.1007/978-3-7643-9964-1_7

Postseismic Deformation Following the 1994 Northridge Earthquake Identified Using the Localized Hartley Transform Filter

2008· book-chapter· en· W4236439260 on OpenAlexaff
K. F. Tiampo, Dawit Assefa, José Fernández, L. Mansinha, H. Rasmussen

Bibliographic record

VenueBirkhäuser Basel eBooks · 2008
Typebook-chapter
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsPrincess Margaret Cancer CentreWestern University
Fundersnot available
KeywordsSuperposition principleDeformation (meteorology)Filter (signal processing)Global Positioning SystemRelaxation (psychology)GeodesySpatial filterViscoelasticitySIGNAL (programming language)GeologySeismologyComputer scienceGeographyMeteorologyPhysicsTelecommunicationsArtificial intelligenceComputer vision

Abstract

fetched live from OpenAlex

Here we present a new mathematical tool, the localized (HL); Bracewell, 1990), that allows for the filtering of 1-D time series through the identification of the power at various spatial and temporal wavelengths. Its application to and the associated results are presented from its application to continuous Global Positioning System (GPS) data from southern California for the time period 1994 through 2006. The HL transform filter removes the high-frequency components of the data and effectively isolates the longer period signal. This long-period signal is modeled as time-dependent postseismic deformation using the viscoelastic-gravitational model of (2004) for six stations selected for their proximity to the Northridge earthquake. The x-, y-, and z-components of the postseismic deformation are compared to the filtered data. Results suggest that this long-period deformation is a result of postseismic relaxation and that the HL transform filter provides an important new technique for the filtering of geophysical data consisting of the superposition of the effects of numerous complex sources at a variety of spatial and temporal scales.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.037
GPT teacher head0.220
Teacher spread0.183 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2008
Admission routes1
Has abstractyes

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