Ground zero for pandemic prevention: reinforcing environmental sector integration
Bibliographic record
Abstract
The global public health sector acknowledges an intact functioning environment as foundational to human health in principle but not in practice.⇒ To effectively prevent pandemics and achieve the United Nations Sustainable Development Goals, it is essential to fully and equitably integrate the environmental sector into global public health and embrace prevention at the source.⇒ The implementation of the WildHealthNet approach in countries such as Cambodia, Viet Nam and the Lao People's Democratic Republic (Lao PDR) has led to the early detection of threats to human and livestock health, manifesting the importance of such wildlife health surveillance systems.⇒ True environmental integration necessitates the creation of innovative institutional partnerships, cross-sectoral policy structures, sustainable funding models and an inclusive conversation involving local communities, Indigenous Leaders, and Traditional Knowledge.
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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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.015 | 0.016 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.039 | 0.003 |
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".