Comparing 10 Year Performance of Cold In-Place Recycling (CIR) with Emulsion Versus CIR with Expanded Asphalt on Highway 7, Perth, Ontario
Bibliographic record
Abstract
Cold In-Place Recycling of hot mix asphalt pavement is an effective pavement rehabilitation strategy with many social, economic and environmental benefits. These include a short construction period, reuse of existing materials, reduction in transportation of materials, reduced greenhouse gas emissions and fuel consumption, and the fact that it is a cost effective treatment. Ontario has been using CIR with emulsified asphalt binder since 1990. CIR is considered to be an established pavement rehabilitation method. The CIR process mills up the existing asphalt pavement, sizes it, mixes in emulsified asphalt, lays the mix back down, and compacts the material without off-site hauling and processing. In 2003, a new development in CIR technology was introduced, using expanded (foamed) asphalt instead of an emulsion to bind the mix. This combination of CIR and expanded asphalt technologies was introduced as Cold In-Place Recycled Expanded Asphalt Mix (CIREAM). The Ministry of Transportation Ontario (MTO) constructed its first trial section of CIREAM on Highway 7, east of Perth in July 2003. Under the same contract, a 5-km trial section of CIREAM was constructed adjacent to 7-km of conventional CIR mix. The performance of these two sections has been monitored over the past 10 years, using the Ministry’s Automated Road Analyzer (ARAN). The results indicate that CIREAM is performing in a similar fashion to conventional CIR. Both treatments are providing excellent long term performance and have been shown to significantly reduce or eliminate reflective cracking.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".