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Record W3008702714 · doi:10.1061/9780784482810.006

Sensitivity and Numerical Analysis Using Strain Space Multiple Mechanism Model for a Liquefiable Sloping Ground

2020· article· en· W3008702714 on OpenAlex
Anurag Sahare, Kyohei Ueda, Ryosuke Uzuoka

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGeo-Congress 2020 · 2020
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsSensitivity (control systems)Mechanism (biology)Geotechnical engineeringGeologyStructural engineeringComputer scienceEngineeringPhysicsElectronic engineering

Abstract

fetched live from OpenAlex

In this paper a model is developed to examine the geo-material variabilities and earthquake motions after calibrating the model by carrying out class C numerical simulation based on dynamic centrifuge test on a liquefiable sloping ground using Ottawa F-65 sand. The constitutive model parameters were derived from the result of cyclic torsional shear test carried out at a relative density of 60%. Following the successful validation with the centrifuge test, the constitutive model is used to carry out sensitivity analysis to ascertain the effect of various uncertainties including the material variability present in situ conditions. In order to understand the behavior of a liquefiable sloping ground under realistic scenario earthquake input motions, a numerical study is also performed under 1995 Kobe and 1989 Loma Prieta earthquake motions and the soil system response is compared.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.808
Threshold uncertainty score1.000

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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