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Record W2128245731 · doi:10.1139/t10-012

Rheological properties of fine-grained sediment: the roles of texture and mineralogy

2010· article· en· W2128245731 on OpenAlexafffundvenue
Sueng Won Jeong, Jacques Locat, Serge Leroueil, Jean‐Philippe Malet

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSiltRheologyGeologyMontmorilloniteSoil waterClay mineralsShear thinningGeotechnical engineeringMineralogyBentoniteSoil scienceMaterials scienceGeomorphologyComposite material

Abstract

fetched live from OpenAlex

Rheological properties of fine-grained sediments depending on index properties and salinity were examined. To characterize flow behaviors as a function of soil type, groups were made for convenience: (i) low-activity clays (group 1), (ii) high-activity clays (group 2), and (iii) silt-rich soils (especially for iron tailings; group 3). Low-activity and high-activity clays have characteristics of pseudoplastic (shear thinning) fluids, and exhibit a decrease in viscosity with increasing shear rate. However, in terms of the change in soil structure due to particle–particle interactions, illitic and montmorillonitic clays have opposite responses to salinity. As most of our data were obtained on low-activity clays — mostly illitic mixtures — we implemented a test program to ascertain the influence of montmorillonite on flow behavior. Using the Bingham model, a simple relationship is presented in terms of the possible critical limits of rheological transitions from clay- to silt- to sand-rich soils.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.662

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 integrity0.0000.001
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 head0.008
GPT teacher head0.175
Teacher spread0.168 · 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 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

Citations117
Published2010
Admission routes3
Has abstractyes

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