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Record W2254017048 · doi:10.1177/096739110801600204

Ldpe/Agave Fibre Composites: Effect of Coupling Agent and Weld Line on Mechanical and Morphological Properties

2008· article· en· W2254017048 on OpenAlexafffund
Simon Leduc, José Ricardo Galindo Ureña, Rubén González‐Núñez, J Ramos Quirarte, Bernard Riedl, Denis Rodrigue

Bibliographic record

VenuePolymers and Polymer Composites · 2008
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité Laval
FundersConsejo Nacional de Ciencia y TecnologíaUniversidad de GuadalajaraUniversité Laval
KeywordsComposite materialLow-density polyethyleneMaterials scienceUltimate tensile strengthFlexural strengthMaleic anhydridePolyethyleneWeld lineAgaveWeldingPolymerCopolymerBotany

Abstract

fetched live from OpenAlex

Natural fibre composites based on Agave fibres (Agave tequilana) and low-density polyethylene (LDPE) were produced by injection moulding. Maleic anhydride grafted polyethylene (MAPE) was also added to study the effect of fibre content, coupling agent addition, and weld line presence on mechanical properties. It was found that tensile and flexural moduli increased with fibre concentration while they decreased for impact strength. In all cases, MAPE addition enhanced the effect up to an optimum content between 2 and 5% on a fibre weight basis. The presence of a weld line substantially reduced tensile properties and this effect could be interpreted in terms of molecular entanglement and orientation changes.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.232
Teacher spread0.213 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations36
Published2008
Admission routes2
Has abstractyes

Explore more

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