U.S. Geological Survey science to support wildlife disease management
Bibliographic record
Abstract
The U.S. Geological Survey (USGS) serves a principal role in conducting wildlife disease outbreak investigations, surveillance, and ecological research to support management of diseases in free-ranging native wildlife.Approximately 60 percent of emerging human infectious diseases such as COVID-19, are zoonotic, meaning they are transmitted between animals and humans and 70 percent of these diseases originate in wildlife (Jones and others, 2008).The effects of emerging wildlife diseases are global and profound, often resulting in economic and agricultural impacts, declines in wildlife populations, and ecological disturbances. Wildlife Disease Outbreak InvestigationsThe USGS Ecosystems Mission Area's Biological Threats and Invasive Species Research Program supports cause-of-death investigations of aquatic and terrestrial wildlife disease outbreaks involving Federal trust species, which includes "migratory birds, threatened species, endangered species, interjurisdictional fish, marine mammals, and other species of concern" (16 U.S.C. 3772(1)), and those outbreaks occurring on Department of the Interior (DOI) managed lands.These diagnostic investigations often lead to research studies to further understand the epidemiology of disease outbreaks and provide tools for disease prevention, detection, and management.Wildlife disease outbreak investigations conducted by USGS scientists support other DOI bureaus (for example, the U.S. Fish and Wildlife Service [USFWS] and National Park Service), as well as State and Tribal natural resource and conservation agencies.The USGS National Wildlife Health Center (NWHC), the only Federal highcontainment facility dedicated to wildlife disease surveillance and research, is registered with the U.S. Centers for Disease Prevention and Control (CDC) Federal Select Agent Program and serves as an affiliate member within USDA's National Animal Health Laboratory Network.For more than 40 years, NWHC diagnostic laboratories have worked collaboratively with Federal, State, and Tribal agencies to investigate wildlife morbidity and mortality events across the Nation.Together, the NWHC and Canadian Wildlife Health Cooperative serve as the World Organisation for Animal Health (WOAH)'s Collaborating Centre for Research, Diagnosis and Surveillance of Wildlife Pathogens.NWHC is also a United Nations Food and Agricultural Organization Reference Centre for Wildlife Health and Wildlife Disease Diagnostics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.231 | 0.131 |
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".