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Record W2954363377 · doi:10.1051/e3sconf/20199202014

Triaxial Simple Shear test: TxSS

2019· article· en· W2954363377 on OpenAlexaffabout
Mourad Karray

Bibliographic record

VenueE3S Web of Conferences · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsHydro-QuébecUniversité de Sherbrooke
Fundersnot available
KeywordsLiquefactionGeotechnical engineeringTriaxial shear testMonotonic functionSimple shearShear (geology)Simple (philosophy)Direct shear testSoil liquefactionGeologyEngineeringMathematics

Abstract

fetched live from OpenAlex

This paper presents a combined triaxial simple shear (TxSS) apparatus developed by the Research Institute of Hydro-Québec (IREQ) in collaboration with the soil dynamics and geotechnical engineering group of the Université de Sherbrooke (Québec, Canada). The TxSS system consists of a simple shear apparatus incorporated in a triaxial cell for the measurements of monotonic and dynamic characteristics of soil samples. A general description as well as some applications and advantages of the TxSS systems over the traditional apparatus are presented. The key application of the TxSS is the evaluation of liquefaction potential of soil under regular or irregular excitations. Test results in terms of monotonic and dynamic characteristics obtained using the TxSS device on different cohesive and cohesionless soil samples are presented to illustrate its capabilities. They are successfully compared to those obtained using reliable design charts available in the literature, conventional apparatus and to those from rigorous numerical analyses.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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 designBench or experimental
Domainnot available
GenreMethods

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
Published2019
Admission routes2
Has abstractyes

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