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Record W4388333444 · doi:10.3390/en16217440

Comprehensive Review of Innovative Materials for Sustainable Buildings’ Energy Performance

2023· article· en· W4388333444 on OpenAlexaff
Yara Nasr, Henri El Zakhem, Ameur El Amine Hamami, Makram El Bachawati, Rafik Belarbi

Bibliographic record

VenueEnergies · 2023
Typearticle
Languageen
FieldEngineering
TopicHygrothermal properties of building materials
Canadian institutionsUniversité de Sherbrooke
FundersEuropean Commission
KeywordsEmbodied energyBuilding envelopeSustainabilityRenewable energyArchitectural engineeringEfficient energy useThermal insulationEnergy performanceEnvironmental economicsEnvironmental scienceCivil engineeringEngineeringThermalMaterials scienceNanotechnologyLayer (electronics)

Abstract

fetched live from OpenAlex

The building sector, one of the most energy-consuming, is among the most current topics due to the maturing concerns about the anthropogenic factor’s impact on CO2 quantities in the atmosphere and its association with global temperature rise. Using sustainable building materials is a promising alternative in building envelope applications to improve in-use energy efficiency. These materials, having a low environmental impact, the advantage of being renewable, and low embodied energy, contribute to global sustainability. This comprehensive literature review presents a broad overview of these materials’ hygrothermal characteristics, thermal performance, and energy use. The main goal is to compile the most important research findings on these materials’ capabilities for building construction and their contributions and effects on energy performance and thermal insulation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.236
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations51
Published2023
Admission routes1
Has abstractyes

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