Regional bridge risk assessment due to the combined effect of flooding and overloading events in Manitoba
Bibliographic record
Abstract
The challenges experienced by Canada’s aging infrastructure require probabilistic methods to address the threats that bridge systems are exposed to. This study provides a framework to evaluate risk associated with two major bridge hazards such as flooding and overloading in Manitoba. The probability of failure of highway bridges due to overloading is assessed as a function of traffic volume and overweight percentages. The probability of failure due to flooding is obtained from a spatial analysis of the water levels. Finally, consequences of failure are established from the analysis of insurance exposure, including climate change effects. Historic data are projected ten years into the future through an ARIMA model. The results of the analysis show that the risk for bridges in the south-west regions of Manitoba is expected to increase by 2035 up to 40% for water levels of 3.0 m and up to 0.6% for a threshold of 12.0 m.
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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 | 0.001 | 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) | 0.000 | 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".