Past, Present, and Future Contributions and Needs for Veterinary Entomology in the United States and Canada
Bibliographic record
Abstract
Nestled between the larger subdisciplines of medical entomology and crop protection, veterinary entomology occupies a unique position in economic entomology. It lies at the intersection of concerns for human pests and disease agent transmission, parasitology in wildlife and natural systems, and integrated pest management in agriculture. Many serious human nuisance pests and disease vectors overlap significantly with animal agriculture. Over the past decade, in fact, the concept of One Health has emerged globally (http://www.onehealthinitiative.com/publications.php). At the core of this concept is the idea that human, animal, and environmental health are linked, and thus should be considered as parts of a larger whole. To that end, we must have scientists who recognize the connections, and this certainly includes veterinary entomologists. For example, cattle operations can produce and provide blood meals for lots of mosquitoes that may later bite people, and house flies developing on animal operations can effectively transfer dangerous bacteria such as Escherichia coli O157:H7 to nearby human populations. Wild birds are the main hosts for key zoonotic arboviruses such as West Nile, and wild rodents harbor the pathogens of plague and Lyme disease. So, the fields of medical and veterinary entomology truly are intimately connected, both operationally and conceptually. This is why they are often treated together in academic courses, and probably should be. Wildlife species themselves suffer tremendously from arthropod pests, ranging from introduced parasitic Philornis spp. flies (Muscidae) now decimating endangered Darwin’s finches (Camarhynchus, Certhidea, and Geospiza spp. [Koop et al. 2011]; Fig. 1A, B) to sarcoptic mange mites (Sarcoptes scabiei [L.]), which can be so virulent that they were once intentionally introduced for biological control of wolves in the American West (Jimenez et al. 2010, Almberg et al. 2012). Heavy infestations of winter tick, Dermacentor albipictus (Packard), possibly influenced by warming conditions and climate change, are killing moose and threatening other wild ruminants in the northern United States and Canada (Fig. 1C; Kutz et al. 2009, https://tinyurl.com/nl4887n).
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 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".