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Record W4383695356 · doi:10.3390/en16145252

The Evolution of Crop-Based Materials in the Built Environment: A Review of the Applications, Performance, and Challenges

2023· review· en· W4383695356 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnergies · 2023
Typereview
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLife-cycle assessmentGreenhouse gasNoveltyEnvironmental impact assessmentRenewable energyCircular economyEnvironmental scienceAgricultureArchitectural engineeringComputer scienceEngineeringEcologyProduction (economics)Economics

Abstract

fetched live from OpenAlex

The use of bio-based building materials as an alternative to replacing concrete or insulation materials is called to become a growing trend in the construction industry. On Science direct, publications concerning “bio-based materials” have increased from 4 in 2002 to 1073 twenty years later, demonstrating a growing interest in these materials However, among bio-based materials, crop or plant-based materials are not as popular. Due to their relative novelty, little is known about their potential applications, physical characteristics, and environmental impacts. The aim of this review is to qualitatively investigate the technical and environmental viability of crop-based materials in modern building applications. The specific objectives of the study consider greenhouse gas (GHG) emissions using life cycle assessment (LCA) approaches, contribution to the circular economy, and physical and hygrothermal characteristics. Another objective is to examine the progress of crop-based materials’ R&D, current bottlenecks, and a future roadmap for their evolution in state-of-the-art renewable buildings. The paper is broad enough to capture a large readership rather than experts in the domain. The review reveals that crop-based materials have the potential to replace traditional, highly emissive building materials. They offer low environmental impacts, in all stages of their life cycle.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score0.212

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 head0.030
GPT teacher head0.245
Teacher spread0.215 · 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