Migrating the City of Calgary from a Static Road Network Definition to a Dynamic Road Network Definition
Bibliographic record
Abstract
Since 1987, the City of Calgary (City) has been using pavement management products to effectively manage their paved road network. As computer technology evolved and the pavement management need of the City changed, the migration from the Municipal Pavement Management Application (MPMA) to state-of-the-art client/server and web (browser-based) Highway Pavement Management Application (HPMA) seemed like a natural transition. HPMA is implemented and used by the Provinces of British Columbia, Alberta, Ontario, and Nova Scotia. Nevertheless, Calgary would be the first municipality in North America to implement HPMA. One of the key reasons motivating the City to move from MPMA to HPMA was the software's capability to handle dynamic segmentation. Migrating the City's data from a static block-to-block segmentation database to a dynamic segmentation database tied to the City's GIS network presented some challenges. This paper presents the challenges encountered during the migration process and how the project team worked together to overcome these challenges. The paper also presents a comparison of results between the MPMA and HPMA databases, including the updated decision trees, the effect of the trees on the pavement network performance, and how the number of pavement sections changed due to dynamic segmentation. The paper also presents the GIS capabilities of displaying the condition of the pavement network. For the covering abstract of this conference see ITRD record number 201310RT334E.
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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 | 0.000 |
| Open science | 0.000 | 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 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".