FULL DEPTH COLD IN-PLACE RECYCLING/STABILIZATION FOR LOW VOLUME ROAD STRENGTHENING : A CASE STUDY
Bibliographic record
Abstract
This paper was presented at the session titled 'Innovative pavement design and evaluation techniques'. Grain transportation rationalization, economic diversification and value added initiatives within the Saskatchewan economy has increased commercial truck traffic on many Saskatchewan roads and will continue to do so in the foreseeable future. These increases in commercial truck traffic hold significant and often-immediate implications for Saskatchewan secondary roads (roads traditionally with ESALs of between 100 and 1000) because many of these roads were not designed to accommodate significant numbers of heavily loaded commercial trucks. Of particular concern, is the approximately 8600 km of thin membrane surfaced (TMS) roads of which many are experiencing accelerated and at times, catastrophic damage. TMS roads are of particular concern because they are expensive to repair once surface breaks occur and TMS roads can be particularly sensitive to truck loading when subgrades are thaw-weakened. As a result, increasing commercial truck traffic has translated into a clear need to strengthen many Saskatchewan TMS and other secondary highways. Although preserving the Saskatchewan secondary road network using conventional methods is both technically feasible and economically tenable in some situations, conventional methods are not economically feasible for many low volume roads in the time frame required to provide an sustainable level of service that serves the immediate needs of the commercial road transport industry across the entire secondary road network. As a result, alternative and innovative road strengthening solutions are required. This paper presents the technical and economic case study of pilot test sections constructed by the Preservation and Operations Branch of Saskatchewan Highways and Transportation to evaluate alternative full-depth cold in-place recycling and strengthening techniques on Control Section 19-06. For the covering abstract of this conference see ITRD number E200883. (A)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".