Transportation Association of Canada Saskatoon, Saskatchewan
Bibliographic record
Abstract
2 With the aging of its infrastructure, Canada is facing a critical problem to deal with the complex and fragmental issues existing in current infrastructure management. Because Bridge Management Systems (BMSs) are not used universally in Canada, this paper aims at reviewing the current state of BMSs in Canada and suggesting an initiative to build a Canadian National Bridge Inventory. The Bridge Expert Analysis and Decision Support (BEADS) system currently used in Alberta is different from the BMSs of other provinces in its system structure and scope. The BEADS is an important part of a comprehensive system-- Transportation Infrastructure Management System (TIMS). The Ontario BMS integrates the deterioration model, cost model, and business rules for treatment selection and costing, and an analytical framework for calculating and representing information relevant to the decision at hand. The Quebec BMS has three main models (Deterioration Model, Treatment Model, and Cost Model) that are used to create work alternatives at the element, project, and program levels. Pontis is used as the BMS in Manitoba. Pontis can support the complete bridge management cycle, including bridge
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.339 | 0.076 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".