Impacts of climate change on indirect human exposure to pathogens and chemicals from agriculture
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
Climate change is likely to affect the nature of pathogens/ chemicals in the environment and their fate and transport. We assess the implications of climate change for changes in human exposures to pathogens/chemicals in agricultural systems in the UK and discuss the effects on health impacts, using expert input and literature on climate change; health effects from exposure to pathogens/chemicals arising from agriculture; inputs of chemicals/pathogens to agricultural systems; and human exposure pathways for pathogens/chemicals in agricultural systems. We established the evidence base for health effects of chemicals/pathogens in the agricultural environment; determined the potential implications of climate change on chemical/pathogen inputs in agricultural systems; and explored the effects of climate change on environmental transport and fate of various contaminants. We merged data to assess the implications of climate change in terms of indirect human exposure to pathogens/chemicals in agricultural systems, and defined recommendations on future research and policy changes to manage adverse increases in risks.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it