Two-Year Experience with Full Depth Reclamation/Stabilization Using Foamed Bitumen in Edmonton, Alberta
Bibliographic record
Abstract
Full Depth Recycling (FDR) and base stabilization has been used by the City of Edmonton since 1992. In 2001 the City of Edmonton, contracted with a local contractor and Wirtgen GmbH for the construction of a demonstration project using foamed bitumen as a stabilizer. In response to the results of the demonstration project, a tender was issued in 2002 for the rehabilitation of 42 lane-kilometres of roadway using foamed bitumen stabilization of the existing road structure. The existing road materials were pulverized, had foamed bitumen added as a stabilizer, were re-graded, and compacted. The process utilized, called for the addition of cement as an active filler. The stabilization proceeded well and provided a smooth, hard, uniform surface suitable for the accommodation of detour traffic. The stabilized base was then overlaid with hot mix asphalt. Upon completion, several of the roadways were chosen for deflection testing to determine the structural improvement and to determine the material moduli. In addition, a series of cores were taken from each roadway to help evaluate the characteristics stabilized material. This paper outlines the work carried out, specifically the condition of the pavements prior to rehabilitation, basic design requirements, construction details, testing, and evaluation completed.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".