MétaCan
Menu
Back to cohort
Record W3135152420 · doi:10.32628/cseit1949143

Influence of Novel Fiber Surface Treatment Method on Morphology and Mechanical Properties of Polypropylene Composites Incorporation of Sisal Fibers

2019· article· en· W3135152420 on OpenAlexaff
Prakash Krishnaiah, Anusuya Devi V S

Bibliographic record

VenueInternational Journal of Scientific Research in Computer Science Engineering and Information Technology · 2019
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsComposite materialMaterials scienceMorphology (biology)SISALPolypropyleneFiber

Abstract

fetched live from OpenAlex

In this study, sisal fibers successfully surface modified by high intensity ultrasound (HIU) and their effects on morphology and mechanical characteristics were investigated for their polypropylene (PP) composites. The SEM analysis shows that after HIU modification, sisal fibers filled PP composites have good compatibility between fibers and PP polymer due to improve the surface roughness. The mechanical properties were significantly enhanced with HIU treated sisal fibers PP composites. The highly cost-effective PP bio-composites reinforced sisal fibers with improved mechanical properties find the potential applications in automotive and other structural engineering industries.

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 score0.004

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 head0.026
GPT teacher head0.295
Teacher spread0.269 · 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

Citations0
Published2019
Admission routes1
Has abstractno

Explore more

Same venueInternational Journal of Scientific Research in Computer Science Engineering and Information TechnologySame topicPolymer Nanocomposites and PropertiesFrench-language works237,207