Slurry surfacing: a review of definitions, descriptions and current practices
Bibliographic record
Abstract
Cold bitumen emulsions (CBE) are currently used worldwide for both non-structural (cold surface treatments) and structural (cold bituminous mixtures) paving applications. Among non-structural applications, bituminous slurry surfacings (BSS) allow to improve surface properties and extend the pavement’s life. However, selection of constituents, mix design, application and quality control procedures for BSS are mostly based on local experience and empirical tests. Thus, the use of BSS is associated to higher technical risks with respect to the use of traditional hot-mix technologies. In this context the RILEM Technical Committee 280-CBE TG2 “Multiphase characterisation of cold bitumen emulsion materials” aims to collect worldwide theoretical knowledge and experiences on BSS and to inspire new standards, specifications and guidelines encompassing the wide set of existing practices. This paper summarizes the first part of the literature review carried out as part of the TC workplan and focuses on the definition, the description and the application method for BSS. National standards, construction specifications and best practice documents from North America, South America, Europe and Australia are analysed and compared.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".