MétaCan
Menu
Back to cohort
Record W4206058647 · doi:10.18280/rcma.310605

A Comparison Between a Solid Block Made of Concrete and Others Made of Different Composite Materials

2021· article· en· W4206058647 on OpenAlexvenueno aff
Emad Toma Karash, Tymor Abed Alsttar Sediqer, Mohammad Takey Elias Kassim

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2021
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
Fundersnot available
KeywordsDeformation (meteorology)Materials scienceComposite numberComposite materialStress (linguistics)Structural engineeringvon Mises yield criterionFiberEngineeringFinite element method

Abstract

fetched live from OpenAlex

In this research, three mathematical models were designed, the first consisting of concrete, the second from carbon fiber, and the third from s-glass fiber, in order to compare the strength of composite materials to different stresses and deformations, because composite materials are better than concrete in terms of weight and shape and do not need to be applied to painting operations in addition to the fact that their thermal insulation is higher than Concrete in high proportions. From the results of the comparison, it was found that the second model was the best model in terms of bearing deformations, as the deformation percentage in it did not exceed the deformation of concrete a lot, reaching (17%), which is a very small percentage, and the stresses towards pregnancy for the second and third models were much better than the bearing of the first model, but the results indicate that the Von Mises Stress in the second model is higher than the first model by a percentage (57%), while the comparison of the third model with the first was the rate of increase percentage (47%).

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.050
GPT teacher head0.311
Teacher spread0.260 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicNatural Fiber Reinforced CompositesFrench-language works237,207