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Record W2321309254 · doi:10.1061/40505(285)14

Combinations of In Situ Tests for Control of Ground Modification in Silts and Sands

2000· article· en· W2321309254 on OpenAlexafffund
John A. Howie, Chris Daniel, Ali Amini Asalemi, R. G. Campanella

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of British Columbia
FundersFu Foundation School of Engineering and Applied ScienceUniversity of British Columbia
KeywordsGeotechnical engineeringCone penetration testPenetration testIn situPore water pressureStress (linguistics)Displacement (psychology)GeologyShear (geology)Deformation (meteorology)Materials scienceComposite material

Abstract

fetched live from OpenAlex

This paper investigates the use of in situ test data to characterize the changes in stress and density induced by ground improvement. Testing comprised seismic cone penetration tests, full displacement pressuremeter tests and resistivity cone penetration tests. After ground treatment, changes were observed in tip resistance, pore pressure response, shear wave velocity, the characteristics of pressuremeter curves and bulk resistivity. Some of these changes can be caused by changes in lateral stress as well as by density increases. The results generally indicate that the use of a combination of in situ tests will improve our understanding of the changes in soil behaviour achieved by ground treatment. The improved understanding of soil behaviour obtained from combinations of tests may allow ground improvement specifications to be written in terms of a desired post-treatment stress-deformation response. However, further research is required to develop reliable methods of characterization of stress-deformation behaviour.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.191

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 head0.009
GPT teacher head0.223
Teacher spread0.215 · 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 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

Citations7
Published2000
Admission routes2
Has abstractyes

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