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Record W3151586500 · doi:10.3390/ma14081848

A State of the Art of the Overall Energy Efficiency of Wood Buildings—An Overview and Future Possibilities

2021· review· en· W3151586500 on OpenAlex
Matheus Roberto Cabral, Pierre Blanchet

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterials · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsUniversité LavalNatural Sciences and Engineering Research Council of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEfficient energy useEmbodied energyArchitectural engineeringCross laminated timberFrame (networking)EngineeringCivil engineeringConstruction engineeringComputer scienceMechanical engineeringEcology

Abstract

fetched live from OpenAlex

The main goal of this study was to review current studies on the state of the art of wood constructions with a particular focus on energy efficiency, which could serve as a valuable source of information for both industry and scholars. This review begins with an overview of the role of materials in wood buildings to improve energy performance, covering structural and insulation materials that have already been successfully used in the market for general applications over the years. Subsequently, studies of different wood building systems (i.e., wood-frame, post-and-beam, mass timber and hybrid constructions) and energy efficiency are discussed. This is followed by a brief introduction to strategies to increase the energy efficiency of constructions. Finally, remarks and future research opportunities for wood buildings are highlighted. Some general recommendations for developing more energy-efficient wood buildings are identified in the literature and discussed. There is a lack of emerging construction concepts for wood-frame and post-and-beam buildings and a lack of design codes and specifications for mass timber and hybrid buildings. From the perspective of the potential environmental benefits of these systems as a whole, and their effects on energy efficiency and embodied energy in constructions, there are barriers that need to be considered in the future.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.019
GPT teacher head0.278
Teacher spread0.260 · 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