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Record W3117279336 · doi:10.18280/acsm.440601

Explicit Study of Epoxy/ Momordica Angustisepala Fiber and Rice Husk Ash Nanoparticle Composites for Roofing Sheet Application

2020· article· en· W3117279336 on OpenAlexvenueno aff
Nwoji Clifford Ugochukwu, Aigbodion Victor Sunday, Adams Mohammed Sani, Obetta Emmanuel Chinonso

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2020
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
FundersUniversity of Johannesburg
KeywordsGalvanizationMaterials scienceCorrosionHuskComposite materialUltimate tensile strengthZincComposite numberMetallurgyLayer (electronics)

Abstract

fetched live from OpenAlex

The development of roofing sheets using sustainable materials to reduce the health hazard pose by asbestos, corrosion of galvanized zinc, and cost of long span aluminum has been giving attention. In this work, density, tensile properties, corrosion resistance and stress analysis of Momordica angustisepala fiber (MAf) and rice husk ash nanoparticle/epoxy composite was used as criteria to determine the suitability of the new material as a roofing sheet application. Roofing sheets of lower weight can be produced with this developed material. The yield strength and tensile strength of 73.45 and 75.12 MPa are within the strength recommended for galvanized zinc and long span aluminum. The new material can be used in the production of roofing sheets with better corrosion resistance than galvanized zinc and long span aluminum. It was established that light weight roofing sheets with better corrosion resistance can be made with this composite.

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 score0.047
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.034
GPT teacher head0.284
Teacher spread0.250 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

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