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Record W2160199740 · doi:10.1002/mame.201000095

Recent Advances in the Application of Natural Fiber Based Composites

2010· article· en· W2160199740 on OpenAlexaff
Jitendra Kumar Pandey, Sung‐Hoon Ahn, Caroline Sunyong Lee, Amar K. Mohanty, Manjusri Misra

Bibliographic record

VenueMacromolecular Materials and Engineering · 2010
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMaterials scienceComposite materialNatural fiberEnvironmentally friendlyMolding (decorative)FiberFlexibility (engineering)CelluloseCellulose fiberChemical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Natural fiber reinforced polymer composites are lightweight, economical and available in a variety of forms. They have low densities, comparable material properties, high molding flexibility and are environmentally friendly, making them a conceivable alternative to traditional fillers like mica, calcium carbonate and glass. By modifying either the resin system or the natural fiber, biocomposites can be designed for different applications ranging from products of commodity to aerospace, examples including electroactive papers, fuel cell membranes, controlled drug release mechanisms and biosensors. This review aims to analyze the advancement in the application of cellulose based materials in different sectors with a discussion of fundamental research in these areas. magnified image

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.208
Teacher spread0.205 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations432
Published2010
Admission routes1
Has abstractyes

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