Impact of shear stress levels on validity of MSCR tests
Bibliographic record
Abstract
Although the MSCR test has become an improvement over the Superpave® |G*|/sinδ parameter, shear stress levels specified in the MSCR test might prove to be too low to successfully represent the stresses occurring in the pavement. To address this hypothesis, five conventional asphalt binders and a total of twelve polymer-modified asphalt blends were tested by MSCR at two different temperatures (50°C and 60°C) as well as five different shear stress levels of 0.1, 3.2, 6.4, 12.8, and 25.6 kPa. The rut results of hot mix asphalts were correlated with the MSCR results. Consequently, better correlations were obtained at higher shear stress levels used in performing MSCR. Moreover, it was shown that MSCR test overestimated the positive effects elasticity on the asphalts’ rut resistance and, thus, more consideration should be given to the asphalt’s ability to resist the applied stresses than to its elastic recovery.
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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 | 0.021 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".