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Record W2166008280 · doi:10.1177/0892705709105965

Effect of Variables on the Mechanical Properties and Maximization of Polyethylene—Aspen Composites by Statistical Experimental Design

2009· article· en· W2166008280 on OpenAlex
Ruijun Gu, B. V. Kokta, Gabriela Chalupova

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

VenueJournal of Thermoplastic Composite Materials · 2009
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceUltimate tensile strengthComposite materialCompatibilizationComposite numberPolyethyleneFiberIzod impact strength testSynthetic fiberPolymerPolymer blend

Abstract

fetched live from OpenAlex

Systemic studies of the effects of the concentrations of maleated polyethylene (MAPE) loading, the content and addition sequence of dicumyl peroxide, the content and type of nanoclay (NC), and aspen fiber loading on the mechanical properties of PE—aspen composites were undertaken with the objective to increase the impact strength as well as the tensile properties. In this article, the formation of an optimal compatibilizing system for the hybrid composite PE—aspen—NC by combining basic principles for compatibilization was investigated. Statistical approach experimentation using Statgraphics Centurion ® with the objective to maximize both the tensile strength as well as the impact properties of natural fiber and nanoclay filled PE was applied to reach values well above that of virgin PE.

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 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 score0.005
Threshold uncertainty score0.574

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 studies0.0000.000
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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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