Wildlife health capacity enhancement in Thailand through the World Organisation for Animal Health Twinning Program
Bibliographic record
Abstract
There is an increasing need for robust wildlife health programs that provide surveillance and management for diseases in wildlife and wild aquatic populations to manage associated risks. This paper illustrates the value of a systematic method to enhancing wildlife health programs. The U.S. Geological Survey and Mahidol University, Faculty of Veterinary Science, Thailand National Wildlife Health Center formally twinned under the auspices of the World Organisation for Animal Health to enhance wildlife health capacity in Thailand and the Southeast Asia Region. We used a system-wide approach to holistically and interdependently enhance capacity. The project commenced with a wildlife health program needs assessment, and capacity enhancement focused on strengthening the general wildlife health surveillance network and improving wildlife health information management. Activities included partner surveys, interactive and didactic workshops, and individual personnel training. Topics included development of wildlife health information management systems, analysis of the current surveillance network, development of a Theory of Change for a strengthened surveillance network, planning workshops to create a wildlife health network, training on wildlife disease outbreak investigation and field sample collection, leading networks, and individual training on bioinformatics and laboratory techniques. Engagement of stakeholders at all levels, continuous communication throughout the project, use of both strategic planning tools and pedagogical methods, and using iterative and adaptive approaches, were key factors to the success of this project.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".