MétaCan
Menu
Back to cohort
Record W2173039148 · doi:10.1139/l07-120

Effects of waste glass additions on the properties and durability of fired clay brickThis article is one of a selection of papers published in this Special Issue on Masonry.

2007· article· en· W2173039148 on OpenAlexafffundvenueabout
S.E. Chidiac, L. M. Federico

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicRecycling and utilization of industrial and municipal waste in materials production
Canadian institutionsMcMaster University
FundersOntario Centres of Excellence
KeywordsDurabilityBrickWaste managementMasonryNon-renewable resourceSustainabilityRaw materialEnvironmental scienceMaterials scienceComposite materialRenewable energyEngineeringCivil engineering

Abstract

fetched live from OpenAlex

The optimization of the production of fired clay brick is essential for the sustainability of the clay brick industry. While there exist areas for improvement of these bricks’ properties when they are used in severe climates, concerns — including nonrenewable resource depletion, increasing energy costs, and waste management — have become increasingly important in Canadian and global industries. One strategy to address these concerns is to use waste additives as fluxing agents in bricks. Use of these additives can decrease the dependency of the industry on nonrenewable resources and can improve brick strength and durability. The effect nonrecycled waste glass additives have on fired brick durability and mechanical and transport properties was investigated in this study. The variables studied were waste glass particle size and percentage added by mass. Microstructure was investigated using mercury intrusion porosimetry to determine the effect on pore structure. The results yielded an optimal percentage addition of waste glass.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.014
GPT teacher head0.185
Teacher spread0.170 · 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

Citations74
Published2007
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicRecycling and utilization of industrial and municipal waste in materials productionFrench-language works237,207