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Record W2047272290 · doi:10.1785/gssrl.76.2.274

Empirical Ground-motion Relations for ShakeMap Applications in Southeastern Canada and the Northeastern United States

2005· article· en· W2047272290 on OpenAlexaffabout
SanLinn I. Kaka, G. M. Atkinson

Bibliographic record

VenueSeismological Research Letters · 2005
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsCitationIconLibrary scienceArchaeologyHistoryGeographyComputer science

Abstract

fetched live from OpenAlex

Other| March 01, 2005 Empirical Ground-motion Relations for ShakeMap Applications in Southeastern Canada and the Northeastern United States Sanlinn I. Kaka; Sanlinn I. Kaka Department of Earth Sciences Carleton University Ottawa, ON KlS 5B6 Canada skaka@ccs.carleton.ca gma@ccs.carleton.ca Search for other works by this author on: GSW Google Scholar Gail M. Atkinson Gail M. Atkinson Department of Earth Sciences Carleton University Ottawa, ON KlS 5B6 Canada skaka@ccs.carleton.ca gma@ccs.carleton.ca Search for other works by this author on: GSW Google Scholar Author and Article Information Sanlinn I. Kaka Department of Earth Sciences Carleton University Ottawa, ON KlS 5B6 Canada skaka@ccs.carleton.ca gma@ccs.carleton.ca Gail M. Atkinson Department of Earth Sciences Carleton University Ottawa, ON KlS 5B6 Canada skaka@ccs.carleton.ca gma@ccs.carleton.ca Publisher: Seismological Society of America First Online: 09 Mar 2017 Online Issn: 1938-2057 Print Issn: 0895-0695 © 2005 by the Seismological Society of America Seismological Research Letters (2005) 76 (2): 274–282. https://doi.org/10.1785/gssrl.76.2.274 Article history First Online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Sanlinn I. Kaka, Gail M. Atkinson; Empirical Ground-motion Relations for ShakeMap Applications in Southeastern Canada and the Northeastern United States. Seismological Research Letters 2005;; 76 (2): 274–282. doi: https://doi.org/10.1785/gssrl.76.2.274 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search Abstract We have developed empirical relations that describe ground-motion amplitudes from earthquakes of 2 < M < 6 at regional distances of 10-500 km in southeastern Canada and the northeastern United States, for ShakeMap applications. The predictive ground-motion parameters are peak ground velocity, peak ground acceleration, and response spectra at frequencies of 1, 2, 5, and 10 Hz. The relations differ from previous relations developed by Atkinson and Boore (1995) in their focus on applicability to the small to moderate regional events important to reliable ShakeMap development. Because of this focus, they are empirical, rather than being based on a stochastic ground-motion model. The stochastic model predictions of Atkinson and Boore (1995) are used at larger magnitudes (M > 4), however, to ensure reasonable values over a broad range of magnitudes (2 to 6).The new relationships are used to estimate ground-motion parameters for ShakeMaps in Ontario. The ShakeMap program combines predicted ground-motion values with recorded ground-motion values to produce an interpolated map of ground-motion amplitudes. It is essential that the predicted ground-motion values be consistent with recorded values in order to generate reliable ShakeMaps. We found that with our new predictive relations, we obtain ground-motion estimates that closely resemble the recorded ground motions for the small events (2 < M < 4) that occur relatively frequently in eastern North America and are often felt. Thus we recommend the use of our predictive relations for ShakeMap applications in southeastern Canada and the northeastern United States. They are not intended for engineering predictions for large rare earthquakes (M > 6). You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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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 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 score0.086
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.305
Teacher spread0.264 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations12
Published2005
Admission routes2
Has abstractyes

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