Comparison of Parameters from a New MSCR Approach with Classical MSCR and LAS Parameters for Simplified Binder Selection
Bibliographic record
Abstract
ABSTRACT Fatigue and rutting are the most studied pavement distresses. There are different material testing protocols whose compatibilities must be systematically analyzed for proper material selection and performance prediction. They usually focus on either rutting or on the fatigue susceptibility of the materials. In asphalt binders, the idea is to assess material behavior that may relate to the behavior of the corresponding asphalt mixtures in the field. However, a new multiple stress creep recovery (MSCR) approach suggests the use of an index obtained from a modified testing protocol (B-index) that may relate to fatigue. This paper compares the parameters obtained by a new MSCR test methodology, which gives parameters that may also relate to fatigue, with parameters from the standard MSCR test and linear amplitude sweep (LAS) test to analyze both binder permanent deformation and fatigue cracking. This study was conducted with a PG (Performance Grade) 64-28 neat binder and three levels of styrene-butadiene-styrene (SBS) modification by weight of the binder: 2 %, 3 %, and 4 %. The results from the new MSCR protocol indicates that the higher the modifier content, the higher the fatigue resistance based on the B-index. This finding is also supported by the LAS parameters, fatigue area factor of binder (FAFB) and af (fracture length). The study concluded that a preliminary choice based on MSCR’s B-index might overcome time-consuming testing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".