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Record W2468398617 · doi:10.15273/ijge.2015.03.013

Seismic Monitoring of a Slope to Investigate Topographic Amplification

2015· article· en· W2468398617 on OpenAlexvenueno aff
Yunsheng Wang, Jianxian He, Yonghong Luo, Shuihe Cao, Zihao He

Bibliographic record

VenueInternational journal of geohazards and environment · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersChina Geological SurveyNational Natural Science Foundation of China
KeywordsEpicenterGeologyAmplification factorRidgeSeismologyPeak ground accelerationMagnitude (astronomy)LandslideDirectivityGeodesyAccelerationGround motion

Abstract

fetched live from OpenAlex

Some earthquakes with a magnitude lower than Ms 7.0, such as Ludian earthquake in Yunnan in 2013, have triggered strong secondary geo-hazards in the form of slope failures. Topographic amplification is generally considered to be the main causal factor for these slope failures. However, until recently, this idea is not supported by appropriate seismic monitoring data. The Kangding Ms 6.3 earthquake on November 22 nd , 2014 was monitored in Lengzhuguan, Sichuan Province, located 56 km from the earthquake epicenter. Six monitoring instruments have recorded this earthquake. The horizontal and vertical component Peak Ground Acceleration (PGA), the site response directivity, the directional variation of the Arias intensity, and the acceleration response spectrum were determined from the data obtained. Conclusions could be drawn that the topographic amplification effect of the isolated ridge on the right bank was stronger than that of nearly linear slope on the left bank and the topographic amplification effect at a slope break was stronger than on a linear slope.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.269

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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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 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

Citations5
Published2015
Admission routes1
Has abstractyes

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