Land use-induced spillover: priority actions for protected and conserved area managers
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
Earth systems are under ever greater pressure from human population expansion and intensifying natural resource use. Consequently, micro-organisms that cause disease are emerging and the dynamics of pathogens in wildlife are altered by land use change, bringing wildlife and people in closer contact. We provide a brief overview of the processes governing 'land use-induced spillover', emphasising ecological conditions that foster 'landscape immunity' and reduce the likelihood of wildlife that host pathogens coming into contact with people. If ecosystems remain healthy, wildlife and people are more likely to remain healthy too. We recommend ten practices to reduce the risk of future pandemics through protected and conserved area management. Our proposals reinforce existing conservation strategies while elevating biodiversity conservation as a priority health measure. Pandemic prevention underscores the need to regard human health as an ecosystem service. We call on multi-lateral conservation frameworks to recognise that protected and conserved area managers are in the frontline of public health safety.
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 | 0.000 | 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