MétaCan
Menu
Back to cohort
Record W2503664978 · doi:10.1139/cgj-2015-0606

Single model establishing strength of dispersive clay treated with distinct binders

2016· article· en· W2503664978 on OpenAlexvenueno aff
Nilo César Consoli, Rubén Alejandro Quiñónez Samaniego, Sérgio Filipe Veloso Marques, Guilherme Irineu Venson, Eduardo Pasche, Luís Enrique González Velásquez

Bibliographic record

VenueCanadian Geotechnical Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsPorosityMaterials sciencePozzolanLimeCompressive strengthComposite materialCuring (chemistry)CementGeotechnical engineeringPortland cementGeologyMetallurgy

Abstract

fetched live from OpenAlex

Dispersive clays experience deflocculation in the presence of somewhat clean still water and are extremely vulnerable to erosion. Lime or Portland cement usage is one of the most applied methods to amend such adverse characteristics and enhance mechanical properties. Present research is aimed at a single power function quantifying the effect of amounts of binder, porosity, and curing period in the assessment of unconfined compressive strength (q u ) of dispersive clay–binder mixtures. Analysing q u results, it was found that a ratio between porosity and binder volumetric content controls the strength of blends. The q u values of the specimens moulded for each binder type were also normalized (i.e., divided by the q u attained at a specific porosity/binder ratio) reaching a single power function quantifying the influence of the binder’s amount, porosity, and curing time. From a pragmatic standpoint, this denotes that carrying out only one unconfined compression test with a specimen moulded with a specific binder, porosity, and cured for a given time period allows to determine an equation that controls the strength for a whole range of porosities and binder contents. The developed normalization was successfully extended to other fine-grained soils treated with cement, lime, and even pozzolan–lime, considering longer curing periods.

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 score0.363
Threshold uncertainty score0.538

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 head0.175
Teacher spread0.166 · 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

Citations25
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil StabilizationFrench-language works237,207