How will climate change impact microbial foodborne disease in Canada?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Foodborne disease is a major concern in Canada and represents a significant climate change-related threat to public health. Climate variables, including temperature and precipitation patterns, extreme weather events and ocean warming and acidification, are known to exert significant, complicated and interrelated effects along the entire length of the food chain. Foodborne diseases are caused by a range of bacteria, fungi, parasites and viruses, and the prevalence of these diseases is modified by climate change through alterations in the abundance, growth, range and survival of many pathogens, as well as through alterations in human behaviours and in transmission factors such as wildlife vectors. As climate change continues and/or intensifies, it will increase the risk of an adverse effect on food safety in Canada ranging from increased public health burden to the emergence of risks not currently seen in our food chain. Clinical and public health practitioners need to be aware of the existing and emerging risks to respond accordingly.
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.
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 | 0.000 | 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 | 0.001 | 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 it