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Record W4400234979 · doi:10.11159/iccste24.243

Sustainable Concrete Design Using Brown Chicken Eggshell to Reduce Carbon Footprint

2024· article· en· W4400234979 on OpenAlexvenueno aff
Camila Sulen, Diego Celis, Sandra Rodríguez, Manuel Muñoz

Bibliographic record

VenueProceedings of the International Conference on Civil, Structural and Transportation Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon footprintFootprintEggshellCarbon fibersSustainable designEnvironmental scienceComputer scienceMaterials scienceSustainabilityComposite materialGreenhouse gasEcologyGeologyComposite numberBiology

Abstract

fetched live from OpenAlex

The construction industry, as well as the food industry, are two influential sectors in the economy of Peru. However, processes such as cement manufacturing for use in concrete production and the disposal of food waste are two of the main causes of environmental pollution globally. This research considers the use of brown chicken eggshell, typically considered waste in the food industry, to be used as a partial replacement for cement in concrete mixes. The experimental work conducted analyses the properties of concrete in a hardened state through destructive and non-destructive laboratory tests, evaluates the effectiveness of eggshell as a partial replacement for cement in three presentations: fresh eggshell, dried eggshell, and eggshell ash; and determines the variation in carbon footprint of the concrete with eggshell compared to the standard concrete mix. This sustainable approach not only improves the properties of concrete but also marks an important step towards sustainable construction and the reuse of food waste.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.489

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 head0.018
GPT teacher head0.224
Teacher spread0.206 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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