Evaluation of a Strain Sweep Tests Protocol as a Tool for Assessing the Homogeneity of SBR Copolymer Composition
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".