Small mammals at the edge of deforestation in Cambodia: Transient community dynamics and potential pathways to pathogen emergence
Bibliographic record
Abstract
Conversion of forest to agricultural land results in rapid and profound changes in ecosystems and biodiversity loss and increases the risk of pathogen emergence. However, insights into the underlying ecological processes linking deforestation and pathogen spillover are required to anticipate and mitigate new pathogen spillovers. Here, we studied small mammal communities and zoonotic pathogens in nine sites in Cambodia where the spatiotemporal deforestation edge was represented by three zones—forest, disturbed, and cleared—within each site. Complete turnover of the small mammal community and species overlap in disturbed forest may provide opportunities for spillover on the spatiotemporal front of forest disturbance. Concurrently, boom-and-bust dynamics of synanthropic species in agricultural landscapes may support the amplification of pathogens in proximity to human settlements. This combination of spillover and amplification may be a key mechanism involved in deforestation-induced pathogen spillovers, highlighting the global health threats of encroaching into natural areas.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".