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Record W2034069904 · doi:10.1002/pc.20143

Preparation and morphology of polypropylene/wood flour composite foams via extrusion

2005· article· en· W2034069904 on OpenAlexaff
Shuwen Zhang, Denis Rodrigue, Bernard Riedl

Bibliographic record

VenuePolymer Composites · 2005
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBlowing agentMaterials scienceWood flourComposite materialExtrusionPolypropyleneComposite numberMoistureWater contentMorphology (biology)Foaming agentPorosityPolyurethane

Abstract

fetched live from OpenAlex

Abstract In this study, polypropylene (PP)/wood flour composites foams with an average cell size lower than 100 μ were successfully produced by extrusion. The effects of the coupling agent (maleated PP), wood flour content (20%, 30%, and 40% weight), initial wood moisture, and blowing agent content on the cell structure are reported. It was found that the addition of a coupling agent increases the blowing agent efficiency and helps to reduce the density of the composites. Moreover, wood moisture appears to be an effective secondary blowing agent under specific conditions. POLYM. COMPOS., 26:731–738, 2005. © 2005 Society of Plastics Engineers

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 score0.002

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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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

Citations56
Published2005
Admission routes1
Has abstractyes

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