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Record W4404617783 · doi:10.1051/e3sconf/202459601045

Sustainable Ceramics: Creating Effective Key Performance Indicators for Industry Monitoring

2024· article· en· W4404617783 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueE3S Web of Conferences · 2024
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsEnvironmentally friendlySustainabilityRenewable energyBusinessEfficient energy useCeramicEnergy consumptionScope (computer science)Environmental economicsEmerging technologiesSustainable developmentEngineeringComputer scienceMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

Sustainable development in the ceramic industry focuses on meeting present needs without compromising future resources. Key strategies include recycling waste, improving energy efficiency, and adopting green technologies. The materials used in creating ceramics, which are very abundant and renewable, are primarily sand or clay, unlike other materials such as real wood. This means that ceramic products are already environmentally friendly right from the start, before the manufacturing process commences. This study discusses environmentally sustainable recycled concrete, using ceramic waste as coarse aggregate in construction. It also discussed how the energy efficiency of buildings can be optimized through thermal energy storage and environmentally friendly materials. This also examined the analysis of Energy Management Systems (EMS) and how they can promote sustainability. The industry is changing with technological innovation using alkali- activated mortars, porous ceramics, and low-carbon technologies. In all their challenges of high energy consumption, green technologies and sustainable practices are crucial in lowering carbon footprints and promoting environmental responsibility. The focus has been made towards the various applications of the ceramic materials in different areas and the benefits associated with them. It can be concluded that the with better technological advancements and research on the design aspects, there is high scope of performance enhancement in the industrial areas.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.787

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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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