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Record W2313029725 · doi:10.1002/app.43692

Characterization and mechanical property of Trinidad coir fibers

2016· article· en· W2313029725 on OpenAlexafffund
Nadira Mathura, Duncan Cree

Bibliographic record

VenueJournal of Applied Polymer Science · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Saskatchewan
FundersForeign Affairs and International Trade CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsUltimate tensile strengthMaterials scienceComposite materialCoirCrystallinityFiberRettingDistilled waterYoung's modulusScanning electron microscopeModulusChemistryBotany

Abstract

fetched live from OpenAlex

ABSTRACT Coir fibers were retted in distilled water (DW) and saline water (SW) for up to 12 weeks. Fibers had diameters of 0.16 mm to 0.56 mm, gauge lengths (GL) of 20 mm and 50 mm, and loaded at strain rates of 5, 20, 40, and 60 mm/min. Tensile strength, Young's modulus, and strain at break properties were evaluated and the results statistically analyzed using analysis of variance (ANOVA). For non‐retted fibers, as the gauge length decreased, the tensile and strain at break increased by 14% and 42%, respectively, while the stiffness increased by 33% for larger gauge lengths. As the fiber diameter decreased, the tensile strength increased from 48.45 MPa to 134.41 MPa for 50 mm gauge length fibers. X‐ray diffraction (XRD) was used to calculate the crystallinity index (CI) of the coir fibers. Secondary electron microscopy was used to assess the fiber surface and fractured area. Although the chemical composition was different, the properties of Trinidad coir fibers were in‐line with coir fibers from other parts of the world making them an ideal material of choice for composites. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133 , 43692.

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 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 score0.019
Threshold uncertainty score0.185

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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 teacher head, 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

Citations31
Published2016
Admission routes2
Has abstractyes

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