Assessing coastal flood risk in a changing climate for the City of Vancouver
Bibliographic record
Abstract
Despite global mitigation efforts, climate change will impact the City of Vancouver’s future. One anticipated impact, sea level rise, is described. A comprehensive understanding of the consequences of these impacts is necessary to guide the process of identifying preferred adaptation strategies. A methodology for a coastal flood risk assessment (CFRA) of sea level rise is provided. The inputs for this risk assessment include inundation mapping and an asset-at-risk inventory. These data sets are combined with flood damage information from Hazus to look at consequences of coastal flooding. There are many uncertainties and gaps in the process of developing a CFRA for a modern, dense, urban city such as Vancouver, particularly when the planning timelines required for preparing and adapting to sea level rise are long. The value of the process and results include increased understanding of hazards and vulnerabilities, and the development of useful visual tools for engagement, planning and education.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".