Zoonotic disease risk at traditional food markets
Bibliographic record
Abstract
Traditional food markets (TFMs) are dynamic and complex systems that play a vital role in societies across the globe. They provide fresh, affordable food, help preserve cultural traditions, and support the livelihoods of millions. However, these markets also present inherent risks associated with the trade of live animals and animal-derived products, including the emergence and spread of zoonotic diseases, which are underreported in these settings. This review explores the dual role of TFMs as essential societal hubs and hotspots for zoonotic diseases, emphasizing the need for surveillance and targeted One Health research on pathogens in these environments. By assessing the health risks associated with the presence of specific animals and their pathogens in TFMs, this review lays the foundation for developing the evidence-based risk assessments and mitigation strategies needed to reduce zoonotic disease risk. Enhancing the safety and sustainability of TFMs through integrated One Health approaches will be crucial for balancing the cultural and economic importance of TFMs with the need for increased global health security.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".