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Record W2055179279 · doi:10.1177/0892705707085347

Effect of Independent Variables on Mechanical Properties and Maximization of Aspen—Polypropylene Composites

2007· article· en· W2055179279 on OpenAlex
Ruijun Gu, B. V. Kokta

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

VenueJournal of Thermoplastic Composite Materials · 2007
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsMaterials scienceComposite materialPolypropyleneUltimate tensile strengthIzod impact strength testComposite numberFiller (materials)FiberGlass fiberWood flourWood-plastic composite

Abstract

fetched live from OpenAlex

Study on the effect of concentration of maleated polypropylene (MAPP), dicumyl peroxide (DCP), nanoclay (NC), and aspen fiber loading on the mechanical properties of Aspen—PP composites has been undertaken with the objective to protect or increase the impact strength without losing or weakening the tensile strength. The central composite design of Statgraphic plus is used to determine the optimum concentration of additives and to maximize both the impact as well as tensile strength properties to be superior to that of pure PP. Finally, the material price of PP composites with an optimal composition of filler (aspen fiber and NC), coupling agent (MAPP), and initiator (DCP) is compared to that of pure PP and PP reinforced with glass fibers.

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)0.002
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 score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.010
GPT teacher head0.231
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