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Record W4391565862 · doi:10.1139/cjce-2023-0280

Determination of the effectiveness of porcelain fine waste to enhance the performance of geopolymer concrete with recycled waste using central composite design and Taguchi method

2024· article· en· W4391565862 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
Fundersnot available
KeywordsTaguchi methodsGeopolymerComposite numberConstruction wasteWaste managementMaterials scienceFly ashComposite materialEngineering

Abstract

fetched live from OpenAlex

This study aims to evaluate the effectiveness of incorporating bone china fine aggregate (BCA) in geopolymer concrete (GPC) with recycled coarse aggregate (RCA). A total of 25 experiments were conducted to optimize the mix design of GPC with coarse RCA and fine BCA. The suitability of a response surface model using the central composite design approach and the Taguchi method with an L25 orthogonal array was assessed. Both methods provide valuable insights and recommendations for achieving ideal mix proportions to enhance strength. The resulting model, with a higher coefficient of determination, successfully predicted the mechanical properties of GPC in fresh and hardened states. The findings suggest that GPC with up to 50% RCA and up to 100% BCA demonstrates optimal performance in terms of hardened mechanical properties. Furthermore, a strong correlation was observed between the predicted and actual values, indicating the reliability of the model.

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.

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)0.001
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 score0.184
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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