MétaCan
Menu
Back to cohort

Durability Evaluation of Green-Engineered Cementitious Composite Incorporating Glass as Aggregate

2020· article· en· W3087710693 on OpenAlexaff
Adeyemi Adesina, Sreekanta Das

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsDurabilityMaterials scienceCementitiousComposite materialAggregate (composite)Composite numberAlkali–silica reactionGlass recyclingCement

Abstract

fetched live from OpenAlex

Rapid awareness about sustainability have ensued in recent times, and there has been a remarkable advancement by the construction industry to incorporate different waste materials into cementitious composites. Recent studies by the authors showed that recycled glass (GL) in the form of beads used as aggregate in engineered cementitious composites (ECC) is beneficial to its mechanical properties. However, with different durability issues related to the use of glass in cementitious composites, evaluating the durability properties of ECC mixtures incorporating glass as aggregate is paramount. Therefore, this study was carried out to evaluate the properties of cementitious composites related to its performance in various environments. The permeability response alongside the resistance to alkali-silica reaction (ASR) of different ECC mixtures incorporating different proportions of GL was evaluated. In addition, microstructural observations were made to understand the microstructural properties of the mixtures evaluated. The results from this study show that the use of glass as aggregates in ECC enhanced the durability properties of the composites.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.248
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.242
Teacher spread0.219 · 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 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

Citations21
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Materials in Civil EngineeringSame topicInnovative concrete reinforcement materialsFrench-language works237,207