National Wildlife Health Center Sylvatic Plague Vaccine and Management of Prairie Dogs
Bibliographic record
Abstract
the University of Wisconsin (UW), have developed a sylvatic plague vaccine that shows great promise in protecting prairie dogs against plague (Mencher and others, 2004; Rocke and others, 2010). Four species of prairie dogs reside in the United States and Canada, and all are highly susceptible to plague and regularly experience outbreaks with devastating losses. Along with habitat loss and poisoning, plague has contributed to a significant historical decline in prairie dog populations. By some estimates, prairie dogs now occupy only 1 to 2 percent of their former range (Proctor and others, 2006), with prairie dog colonies being now much smaller and fragmented than they were historically, making individual colonies more vulnerable to elimination by plague (Antolin and others, 2002). At least one species, the Utah prairie dog (Cynomys parvidens) is listed by the U.S. Fish and Wildlife Service (FWS) as “threatened”. Controlling plague is a vital concern for ongoing management and conservation efforts for prairie dogs. Sylvatic Plague: A Continued Threat to North American Wildlife Sylvatic plague, caused by Yersinia pestis, is a bacterial disease transmitted by fleas that afflicts many mammalian species, including humans. For many species of wildlife, plague mortality is a serious conservation issue. In fact, more than half of North American rodent species considered of
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".