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Record W4385303849 · doi:10.18280/acsm.470306

Evaluation of Some Beneficial Environmental Impacts and Enhanced Thermal Properties Resulting from Waste Plastic Integration into Concrete

2023· article· en· W4385303849 on OpenAlexvenueno aff
Faez Ahmed Salih, Fathoni Usman, Gasim Hayder, Yasir Al-Ani

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2023
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsnot available
Fundersnot available
KeywordsPlastic wasteSustainabilityPlastic pollutionEnvironmental scienceEnvironmental pollutionWaste managementWaste recyclingEnvironmentally friendlyPollutionEnvironmental protectionEngineering

Abstract

fetched live from OpenAlex

The burgeoning issue of plastic waste, exacerbated by urbanization and pollution, has emerged as a global concern.A novel approach to address this problem involves the recycling of waste plastics and their incorporation into concrete, thereby promoting sustainability and environmental responsibility.This study offers a comprehensive review of the effects of integrating plastic waste into concrete to enhance its thermal properties.The findings reveal that the inclusion of waste plastics considerably reduces the thermal conductivity of concrete, augments its thermal resistance, and optimizes its thermal diffusivity.Moreover, the utilization of plastic waste in concrete yields environmental advantages, such as the mitigation of detrimental impacts on marine and terrestrial ecosystems resulting from plastic pollution.This research contributes to the expanding body of literature on sustainable concrete production and waste plastic recycling, providing valuable insights for the development of eco-friendly construction materials.

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)0.001
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 score0.293
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.045
GPT teacher head0.264
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.

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

Citations9
Published2023
Admission routes1
Has abstractyes

Explore more

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