Emerging infectious disease: An underappreciated area of strategic concern for food security
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
Emerging infectious diseases (EIDs) increasingly threaten global food security and public health. Despite technological breakthroughs, we are losing the battle with (re)emerging diseases as treatment costs and production losses rise. A horizon scan of diseases of crops, livestock, seafood and food-borne illness suggests these costs are unsustainable. The paradigm of coevolution between pathogens and particular hosts teaches that emerging diseases occur only when pathogens evolve specific capacities that allow them to move to new hosts. EIDs ought to be rare and unpredictable, so crisis response is the best we can do. Alternatively, the Stockholm Paradigm suggests that the world is full of susceptible but unexposed hosts that pathogens could infect, given the opportunity. Global climate change, globalized trade and travel, urbanization and land-use changes (often associated with biodiversity loss) increase those opportunities, making EID frequent. We can, however, anticipate their arrival in new locations and their behaviour once they have arrived. We can 'find them before they find us', mitigating their impacts. The DAMA (Document, Assess, Monitor, Act) protocol alters the current reactive stance and embodies proactive solutions to anticipate and mitigate the impacts of EID, extending human and material resources and buying time for development of new vaccinations, medications and control measures.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.000 | 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