Integrated Road Research Facility (IRRF): An Alberta Research Initiative
Bibliographic record
Abstract
The Integrated Road Research Facility (IRRF) was founded in 2012 through an innovative partnership between the University of Alberta, Alberta Transportation, Alberta Recycling, the City of Edmonton and Canada Foundation for Innovation (CFI). The IRRF includes a fully instrumented test road, located approximately 15 km east of downtown Edmonton. The test road has three major test sections that focus on evaluation of: 1) two road embankment materials: Tire Derived Aggregate (TDA) made from Passenger-Light-Truck-Tire (PLTT) and Off-the-Road (OTR) tires and PLTT-soil mixture; 2) flexible pavement performance in cold-climate conditions; and 3) insulated pavement sections using polystyrene boards, bottom-ash and TDA. The test road is unique in Canada and more than 8,000 tonnes of recycled tires were used in the construction of the road. The test road was instrumented with more than 250 pavement and geotechnical instrumentation during construction. Geotechnical instrumentation is used to monitor the TDA sections' compression behavior, internal temperature and drainage characteristics. Instrumentation in the insulation layer test section monitors temperature, moisture and frost penetration. Instrumentation in the pavement performance sections monitors the mechanistic responses of the pavement to both truck traffic and environmental conditions. This paper discusses details regarding the instrumentation design, installation procedure and data collection system for the three test sections. The results of Falling-Weight-Deflectometer (FWD) tests performed on finished subgrade for uniformity evaluation are also presented and discussed. (A) For the covering abstract of this conference see ITRD record number 201310RT334E.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.008 |
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".