Cold recycling of reclaimed asphalt with bituminous binders: A critical comparison of practices in the countries involved in the TC 308-PAR TG1 – Part I
Bibliographic record
Abstract
The RILEM technical committee on Performance-based Asphalt Recycling TC 308-PAR focuses on research, knowledge exchange and dissemination on the asphalt material recycling. Specifically, the Task Group 1 (TG1) “Performance-based Evaluation of Cold Recycled Asphalt Mixtures” aims at matching laboratory testing methods with the in-service behavior of cold recycled asphalt mixtures. In this context, the TG1 members collaborated to share the different cold recycling procedures used in their respective countries, with the goal of comparing specific practices, technical requirements, and performance expectations. Considering the different areas of expertise and application environments, such as road type, traffic volume, climate and material resources, the information gathered provides a broad framework of the current practices and prospects a widening of future application of cold recycling techniques. The comparison among country practices was divide into two papers: Part I dealing with constituent materials and common mixture composition and requirements and Part II treating testing procedures and mechanical characteristics. Particularly, Part I reports a critical comparison between standard frameworks for reclaimed asphalt (RA), cold recycling practices, materials and mixtures used in Italy, Canada, Poland, Brazil and USA, either adopted by selected road administrations or established by reference standards.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".