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Record W2583122919 · doi:10.1785/0220160153

Are Ground‐Motion Models Derived from Natural Events Applicable to the Estimation of Expected Motions for Induced Earthquakes?

2017· article· en· W2583122919 on OpenAlexaffabout
Gail M. Atkinson, K. Assatourians

Bibliographic record

VenueSeismological Research Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsCitationIconDownloadLibrary scienceHistoryComputer scienceOperations researchWorld Wide WebEngineering

Abstract

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Research Article| February 01, 2017 Are Ground‐Motion Models Derived from Natural Events Applicable to the Estimation of Expected Motions for Induced Earthquakes? Gail M. Atkinson; Gail M. Atkinson aDepartment of Earth Sciences, Western University, London, Ontario, Canada N6A 5B7gmatkinson@aol.com Search for other works by this author on: GSW Google Scholar Karen Assatourians Karen Assatourians aDepartment of Earth Sciences, Western University, London, Ontario, Canada N6A 5B7gmatkinson@aol.com Search for other works by this author on: GSW Google Scholar Author and Article Information Gail M. Atkinson aDepartment of Earth Sciences, Western University, London, Ontario, Canada N6A 5B7gmatkinson@aol.com Karen Assatourians aDepartment of Earth Sciences, Western University, London, Ontario, Canada N6A 5B7gmatkinson@aol.com Publisher: Seismological Society of America First Online: 14 Jul 2017 Online Issn: 1938-2057 Print Issn: 0895-0695 © Seismological Society of America Seismological Research Letters (2017) 88 (2A): 430–441. https://doi.org/10.1785/0220160153 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Gail M. Atkinson, Karen Assatourians; Are Ground‐Motion Models Derived from Natural Events Applicable to the Estimation of Expected Motions for Induced Earthquakes?. Seismological Research Letters 2017;; 88 (2A): 430–441. doi: https://doi.org/10.1785/0220160153 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 Natural earthquakes in western North America can be reasonable proxies for induced earthquakes in central and eastern North America because of the opposing effects that source depth and tectonic setting have on the stress parameter that scales high‐frequency ground‐motion amplitudes. It is critical that ground‐motion prediction equations selected as induced‐event proxies have appropriate near‐distance scaling behavior for small‐to‐moderate shallow events. In this article, we describe the conditions under which natural‐earthquake models are suitable for induced‐seismicity applications. Using examples from Oklahoma and Alberta, we identify at least three models (Abrahamson et al., 2014; Atkinson, 2015; Yenier and Atkinson, 2015b) that are reasonable proxy estimates of median motions from induced earthquakes in the east for the magnitude–distance range of most concern to hazard estimation from such events: M 3.5–6 at distances to 50 km. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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)0.002
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.109
GPT teacher head0.343
Teacher spread0.234 · 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 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

Citations36
Published2017
Admission routes2
Has abstractyes

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