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Record W2770175865 · doi:10.15376/biores.13.1.cogulet

The Multifactorial Aspect of Wood Weathering: A Review Based on a Holistic Approach of wood Degradation Protected by Clear Coating

2017· review· en· W2770175865 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

VenueBioResources · 2017
Typereview
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWeatheringDegradation (telecommunications)CoatingMaterials scienceComposite materialPulp and paper industryEngineeringGeologyGeochemistry

Abstract

fetched live from OpenAlex

Wood is an abundant and renewable natural resource. Its use is promoted as a way to reduce the carbon footprint in building construction. Wood structures are degraded by their environment due to weathering. This review is a meta-analysis of the main factors of degradation that belong to this phenomenon. The impact of irradiation, the role of water, oxygen, temperature, and colonization by fungi are explained. To protect against these factors, the use of coatings is the most common solution. Since currently the trend is to maintain the grain and the natural color of the wood, the use of transparent coatings is favored. This review presents the main technologies used in clear wood coatings. The durability of this protection against weathering is approached. The whole of knowledge gathered has made it possible to begin a discussion on the multifactorial aspect of wood weathering. Schemes were created to synthesize the synergistic and antagonistic effects between the degradation factors.

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 score0.956
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.104
GPT teacher head0.300
Teacher spread0.195 · 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