Evaluation of Warm-Mix Asphalt Produced with the Double Barrel Green Process
Bibliographic record
Abstract
During the past 3 years, warm-mix asphalt (WMA) technologies from European countries have entered the North American market. European experiences with WMA technologies have indicated that a significant reduction in mixture temperature, mixture viscosity, energy consumption, and environmental emissions during asphalt mix production and placement can be achieved in comparison with traditional hot-mix asphalt (HMA). On the basis of North American experiences with these technologies to date, transportation agencies and HMA producers are unlikely to adopt WMA technologies solely for the reduction in manufacturing energy costs and environmental emissions, because these benefits do not cover the associated increase in investment and additive costs of WMA over HMA, even in the most expensive North American energy markets. This paper presents an evaluation of the economic, environmental, and mixture performance factors to assess the sustainability of WMA in North America. The paper examines the benefits, risks, investment and material costs, and sustainability associated with the different WMA technologies and specifically the Double Barrel Green process. Included is a mixture performance evaluation of WMA mixes containing reclaimed asphalt pavement and Manufactured Shingle Modifier produced with the Double Barrel Green System during field trials in Vancouver, British Columbia, Canada.
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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 | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".