2014 Manitoba Southwest Region Bridge Flood Response and Recovery
Bibliographic record
Abstract
In July 2014, the southwest corner of Manitoba experienced an unprecedented high water level event due to near record precipitation that occurred at the end of June. This rain event caused bridge collapses, major culvert failures and road closures, impacting over 100 bridge structures owned by Manitoba Infrastructure and Transportation (MIT), crippling local access and transportation in the area. The Assiniboine River system also simultaneously experienced a record high water level event, similar to previous record flood levels in 1976 and 2011, putting several major MIT bridges at risk. A state of emergency was declared by the Province of Manitoba in portions of the province and 60 Manitoba rural municipalities declared a state of local emergency in response to flood water impacts. MIT bridge and highway personnel were tasked with responding to this flood event to assess damage and determine plans of action to restore access to flood damaged bridge and road infrastructure. An estimated $70 million in damage occurred to MIT’s bridges and province-wide, an estimated $220 million in damage for Disaster Financial Assistance, related to the 2014 summer flooding, was sustained. This paper will expand on the following points: 1. The background of the flood event and affected areas; 2. The impact to the area residents and stakeholders, including oil production companies and agricultural producers in the region; 3. MIT’s action plan implemented immediately during the flood event; 4. How MIT personnel assessed flood damage to structures; 5. How MIT temporarily repaired bridge and culvert structures to re-establish interim restricted access; and 6. MIT’s process for fast-tracking replacement of severely damaged structures by direct negotiations with engineering service.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".