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Record W2789109956 · doi:10.1139/cgj-2017-0599

Laboratory assessment of semi-permeable properties of a natural sodium bentonite

2018· article· en· W2789109956 on OpenAlexvenueno aff
Andrea Dominijanni, Nicolò Guarena, Mario Manassero

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsBentoniteSodiumPore water pressureThermodynamicsSwellingDiffusionChemistryMaterials scienceVoid (composites)Geotechnical engineeringMineralogyGeologyComposite materialPhysics

Abstract

fetched live from OpenAlex

The relevance of the semi-permeable properties of bentonites, which affect both their transport processes and mechanical behaviour, has been assessed through the experimental determination of three parameters: the reflection coefficient, ω; the osmotic effective diffusion coefficient, [Formula: see text]; and the swell coefficient, ϖ. Two multi-stage tests were conducted on a natural sodium bentonite, while varying both the specimen void ratio, e, and the solute concentration, c s , of the equilibrium sodium chloride (NaCl) solutions. The measured phenomenological parameters were interpreted through a mechanistic model, in which the electric charge of clay particles is taken into account via a single material parameter, [Formula: see text], referred to as the “solid charge coefficient”. A constant value of [Formula: see text] = 110 mmol/L was found to provide an accurate interpretation of the experimental data, at least within the investigated range of bentonite void ratios (3.33 ≤ e ≤ 4.18) and NaCl concentrations of the external bulk solutions (5 ≤ c s ≤ 90 mmol/L). The results support the hypothesis that both chemical osmosis and swelling pressure are macroscopic manifestations of the same interactions, which occur at the microscopic scale between the clay particles and the ions contained in the pore solution, and that both of them can be modelled through a single theoretical framework.

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 score0.592
Threshold uncertainty score0.422

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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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

Citations50
Published2018
Admission routes1
Has abstractyes

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