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Record W2805429629 · doi:10.1139/cgj-2018-0016

Effects of sampling disturbance in geotechnical design

2018· article· en· W2805429629 on OpenAlexvenueaboutno aff
Guan Tor Lim, Jubert Pineda, Nathalie Boukpeti, J. Antônio H. Carraro, Andy Fourie

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringSampling (signal processing)LeveeSettlement (finance)Soil testSoil waterGeologyEnvironmental scienceEngineeringSoil scienceComputer science

Abstract

fetched live from OpenAlex

This paper describes an experimental study of the effects of sampling disturbance in an Australian natural soft clay and the consequences of different sample quality on the representativeness of soil parameters used in geotechnical designs. The paper is divided into three sections. Laboratory test results obtained from specimens retrieved using three different tube samplers as well as the Sherbrooke (block) sampler are first described. Then, the sample quality assessment, using available indices proposed for soft soils, is presented. It is shown that sample quality varies with the stress paths and boundary conditions applied in laboratory tests. Finally, mechanical soil properties derived from specimens retrieved using the different samplers are used in the prediction of two classical problems in soil mechanics: the settlement and excess pore pressure response underneath an embankment as well as the settlement and bearing capacity of a shallow footing. These two examples are used here to highlight the consequences of poor sampling in practice.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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.

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

Citations34
Published2018
Admission routes2
Has abstractyes

Explore more

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