Evaluation of Asphalt Binder Characteristics of Typical Ontario Superpave CRM and RAP-HMA Mixtures
Bibliographic record
Abstract
Utilization of Reclaimed Asphalt Pavement (RAP) and Crumb Rubber Modifiers (CRM) in Hot Mix Asphalt (HMA) offers transportation agencies the opportunity of enhancing the functional properties of the mixture and reducing construction costs, thus creating an engineered value-added application. Consequently, these resources are reused as opposed to being disposed in a landfill. However, a successful utilization entails evaluating engineering properties of the asphalt binder and the mechanistic properties of hot mix asphalt concrete produced using varying amounts of RAP and CRM compositions. This paper presents the results of a study to characterize and evaluate the performance of asphalt binders extracted from an array of laboratory and plant-prepared Ontario Superpave HMA mixtures containing up to 40% RAP in combination with varying CRM compositions. Such binders were characterized in accordance with the Superpave performance-based specification.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".