Gradation and Performance Research of Cold Recycled Mixture
Bibliographic record
Abstract
Cold in-place recycling was adopted for a project in China due to the availability of reclaimed asphalt pavement (RAP). Based on the Foshan loop project in Guangdong, the gradation design of cold recycled mixtures (CRM) was optimized by the Bailey Method. Emulsified asphalt and cement were used as additives. Then, the screenings of aggregates in RAP and RAP were analyzed and compared. Additionally, new aggregates and cement were added to dispose the framework structure of the cold recycled mixture, and modified Marshall Tests conducted to determine the optimum amount of emulsified asphalt and water, by which cold recycled mixture was formed and performance experiments of asphalt mixture carried out. Eventually, the results show that the gradation design of cold recycled mixture needs to be adjusted by the screening of aggregates in RAP. Also, cold recycled mixture is suitable for highway sub-grade and pavements of low-grade roads.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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".