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Record W2032625248 · doi:10.1080/00914030008054859

Durability of Wood Flour-Thermoplastic Composites under Extreme Environmental Conditions and Fungal Exposure

2000· article· en· W2032625248 on OpenAlex
Mikhail Khavkine, M. Kazayawoko, Samuel Law, John J. Balatinecz

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.

Bibliographic record

VenueInternational Journal of Polymeric Materials · 2000
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWood flourComposite materialMaterials sciencePolyethyleneCompoundingFlexural strengthBoilingWood-plastic compositeSwellingMoistureComposite numberChemistry

Abstract

fetched live from OpenAlex

Abstract The main purpose of this research work was to investigate the response of wood flour reinforced polyethylene composites to 2 hours water boiling, five complete boiling and freezing cycles and fungal (Gloeophyllumm Traebum/Brown-rot fungus) exposure. Five composite formulations were manufactured and analyzed (0, 50, 60, 70 and copper carbonate treated 60% wood flour/polyethylene composites). The results showed that wood flour loading decreased the resistance of the composites to moisture and fungal environment. The exposure of the composites to 2 hours water boiling and five complete boiling and freezing cycles caused serious damage to the interfacial adhesion between wood flour and polyethylene matrix due to contraction and swelling stresses developed during cyclic exposure. The addition of 1 percent copper carbonate salt during compounding of wood flour and polyethylene prevented the colonization and proliferation of fungus on the surface of the composites, but had a negative effect on the water uptake and flexural properties of the composites.

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 categoriesInsufficient payload (model declined to judge)
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 score0.023
Threshold uncertainty score0.987

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)0.0140.000

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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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