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Record W2898545030 · doi:10.1139/cgj-2018-0310

Colloidal aspects of incompatibility reactions of bentonite with saline leachates as indicated from a modified fluid loss test

2018· article· en· W2898545030 on OpenAlexvenueno aff
András Fehérvári, Will P. Gates, Yang Liu, Abdelmalek Bouazza, Alla Marchuk, Serhiy Marchuk, Terence W. Turney, Antonio F. Patti

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
FundersAustralian Research CouncilMonash UniversityUniversity of Glasgow
KeywordsBentoniteColloidFlocculationLeachateSettlingDewateringGeotechnical engineeringMaterials scienceGeologyChemical engineeringChemistryEnvironmental engineeringEnvironmental scienceEngineeringEnvironmental chemistry

Abstract

fetched live from OpenAlex

The fluid loss test has been used by geotechnical engineers for rapid evaluation of the hydraulic barrier properties of bentonites. In this study, a modified fluid loss test, along with viscometric and electrophoretic mobility measurements, was used to assess the colloidal interactions of three powdered sodium bentonites with saline leachates, namely 0–2 N solutions of NaCl and CaCl 2 . The results indicate that the fluid loss test provides robust and reliable information on the water retention of bentonite; moreover, it gives information on the aggregate structure, size, and settling of bentonite flocs and on the high-salt stabilization phenomena (packing and densification of clay aggregates) in saline leachates. Quantifying the water retention characteristics, along with the colloidal (i.e., flocculation) behaviour, using the fluid loss test, provides detailed understanding of barrier properties of bentonites important for various applications (e.g., barrier systems, dewatering).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score0.999

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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 designObservational
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

Citations3
Published2018
Admission routes1
Has abstractyes

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