Performance of home of flood resiliency and flood retrofit measures
Bibliographic record
Abstract
This report outlines a study funded by Architecture Sans Frontières Québec (ASFQ) and Canada Mortgage and Housing Corporation (CMHC) as part of the “Building for the Future” initiative. Flooding remains the costliest natural hazard worldwide, with damage exceeding US$320 billion from 2018 to 2023. Increasing instances of flooding, fueled by climate change, aging infrastructure and extreme weather conditions, present serious risks, particularly in Canada, where 80% of cities are located in flood-prone areas. With a significant proportion of Canada's real estate stock located in flood-prone areas, cost-effective solutions are essential to protect these properties. This project aims to: • Evaluate the effectiveness of Canadian building standards against the effect of floods. • Evaluate various temporary residential flood barriers under different conditions. • Develop experimental protocols in line with existing international standards. Two phases of testing were carried out at the National Research Council of Canada (NRC): Phase 1: focused on assessing performance (leakage rates) through standard Canadian residential construction. Phase 2: evaluated the performance of various temporary opening flood barriers in two experimental setups. This study highlights the critical need for adaptable, standardized flood protection measures tailored to Canadian contexts. While many of the proprietary flood barriers tested showed promise, performance inconsistencies under real-world conditions underscore the need for rigorous, standardized testing. The knowledge gained here has laid the foundation for future research, policy development and public adoption of effective flood mitigation strategies. This study is one of the first in the world to comprehensively compare temporary opening barriers (traditional and proprietary) in a three-dimensional flood environment with waves and debris impacts. The knowledge gained from this study will assist the general public in barrier selection and serve as a benchmark for the development of improved testing standards in Canada. The results of this study will be forwarded to the CSA working group developing the standard for temporary flood barriers. The project also contributed to the training of four highly qualified people at INRS: two undergraduate research trainees and two doctoral students.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".