Alberta Road Weather Information Systems Network Expansion, Winter Risk Assessment and Priority List for Advanced Winter Maintenance Strategies
Bibliographic record
Abstract
In 2003, Alberta Transportation (AT) completed an Advanced Traveller Information System (ATIS) and Advanced Transportation Management System (ATMS) Blueprint project. Part of this project was to determine where Road Weather Information Systems (RWIS) sites should be located on the National Highway System (NHS) to provide the optimal coverage. After deployments it was recognized that coverage solely on the NHS resulted in gaps in the real-time and forecast road condition information throughout the province. In 2008, AT undertook an RWIS expansion study to identify the gaps and determine which technology would best provide the relevant road weather information necessary to support winter maintenance activities. The expected outcome of this project is a consistent coverage across the province which will redefine current maintenance levels on a regional basis, reduce priority based maintenance activities, and help in the continued provision of a consistent level of service. Based on the relative ranking of the risk and a short list of winter risk mitigation strategies, AT was provided with a relative ranking and priority list for deployment of advanced winter maintenance technologies. This paper will discuss the regional and micro level RWIS assessments that were completed. It will also review the risk assessment which identified the locations with a high winter collision risk. Finally, the paper will overview the resulting deployment plan which recommended approximately 20 RWIS sites on the provincial highway system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".