Performance evaluation of crumb rubber and paraffin modified stone mastic asphalt
Bibliographic record
Abstract
Recently, crumb rubber (CR) obtained from waste tires and Fischer–Tropsch paraffin are mostly used in bitumen modification to improve the performance of bituminous mixtures. Each of these additives affects the different properties of mixtures. There are limited studies in the literature about the combined usage of additive in the same mixture to utilize the different characteristics. In this study, the stability, stiffness, fatigue resistance, permanent deformation resistance, and moisture susceptibility characteristics of the stone mastic asphalt prepared with the bitumen modified with CR and paraffin were examined and compared with the control mixture. It was determined that CR-modified mixtures showed significantly more elastic characteristics. The mixture in which the 10% CR and 3% paraffin were used together gave better results in terms of moisture susceptibility and fatigue resistance when compared with the control mixture. It was determined that the use of paraffin together with CR contributed to the improved performance, and was in accordance with the CR in terms of mechanical characteristics of stone mastic asphalt.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".