Recreational water illness in Canada: a changing risk landscape in the context of climate change
Bibliographic record
Abstract
Swimming and other recreational water activities at public beaches are popular outdoor leisure activities among Canadians. However, these activities can lead to increased risks of acquiring acute gastrointestinal illness and other illnesses among beachgoers. Young children have much higher rates of exposure and illness than other age groups. These illnesses have a significant health and economic burden on society. Climate change is expected to influence both the risk of exposure and illness. A warming climate in Canada, including more severe summer heatwave events, will likely lead to increased recreational water use. Warmer temperatures will also contribute to the growth and increased range of harmful algal blooms and other climate-sensitive pathogens. Increased precipitation and heavy rainfall events will contribute to fecal and nutrient contamination of beach waters, increasing risks of gastrointestinal illness and harmful algal bloom events. There is a need to enhance recreational water research and surveillance in Canada to prepare for and adapt to these changing risks. Key research and policy needs are suggested and discussed, including evaluating and monitoring risks of recreational water illness in Canadian contexts, improving timely reporting of recreational water quality conditions, and enhancing approaches for routine beach water surveillance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".