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Record W4393309820 · doi:10.6000/1929-5995.2024.13.02

Evaluation of a Strain Sweep Tests Protocol as a Tool for Assessing the Homogeneity of SBR Copolymer Composition

2024· article· en· W4393309820 on OpenAlexvenueno aff
Harrison Lourenço Corrêa, Cristina R. G. Furtado

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2024
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsnot available
FundersFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
KeywordsHomogeneity (statistics)Materials scienceCopolymerComposite materialPolymerComputer science

Abstract

fetched live from OpenAlex

Global competition in products and services demands constant improvement in production systems. Similarly, it is essential for industries to have quality control tools capable of assessing the compliance of a given product at a lower cost and with greater effectiveness. In the rubber and composite industry, where complex formulation and mixing systems can affect not only the quality of the final product but also the processing of rubber, the development of a protocol that assumes this function is important. The present study developed samples of elastomeric blends based on styrene-butadiene copolymer (SBR) with different filler concentrations (30, 60, and 90 phr of ground tire rubber as filler), which were analyzed using an oscillating cavity rheometer (MDpt-TechPro). Based on a proprietary testing protocol, the degree of homogeneity of the composites was evaluated, which was compared with scanning electron microscopy studies. The implemented protocol, which provides results within 30 minutes, proved to be promising for quality control of these blends, and it can be used by rubber processing industries, saving both time and cost, being an unprecedented study on the 'homogeneity-rheology' relationship.

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)0.028
metaresearch head score (Gemma)0.001
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 score0.027
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0280.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
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 head0.120
GPT teacher head0.491
Teacher spread0.371 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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