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Record W2101237664 · doi:10.1139/t09-113

Mechanical characterization of matrix coarse-grained soils with a large-sized triaxial device

2010· article· en· W2101237664 on OpenAlexvenueno aff
Bassel Seif El Dine, Jean-Claude Dupla, Roger Frank, Jean Canou, Y. Kazan

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterGeotechnical engineeringMatrix (chemical analysis)GeologyMaterials scienceSoil scienceComposite material

Abstract

fetched live from OpenAlex

This paper presents an experimental program that characterizes the mechanical behavior of heterogeneous soils using a large-sized triaxial apparatus (300 mm diameter and 600 mm height). A particular class of heterogeneous soil called matrix coarse-grained soil, composed of a mixture of a sandy matrix (Fontainebleau sand) and inclusions (gravels), was studied. The experimental procedure to rebuild samples is presented first with a description of a typical test setup. A synthesis of the experimental results obtained is then presented. A particular focus is placed on studying the influence of basic soil parameters: the properties of the inclusions (volumetric fraction, particle size, grading parameter) and the initial state of stress in the soil. The two classical methods used to study the mechanical properties of matrix coarse-grained soils in the laboratory (clipping and clipping-substitution) are evaluated.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.199
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
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

Citations104
Published2010
Admission routes1
Has abstractyes

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