Pathogenicity of biological control agents for livestock ectoparasites: a simulation analysis
Bibliographic record
Abstract
The management of arthropod ectoparasites of livestock currently relies largely on the use of neurotoxic chemicals. However, concerns over the development of resistance, as well as operator and environmental contamination, have stimulated research into alternative approaches to their control, including the use of biological pathogens. The search for suitable pathogens often focuses on identifying the most highly virulent agents for application. However, practical issues such as the ability of a pathogen to penetrate to the skin through hair or wool, tolerance of high skin surface temperatures and high residual activity may mean that the most virulent pathogens are not necessarily the most appropriate for commercial application. Here, a simulation model is constructed and used to highlight a range of key features which characterize suitable pathogens for such application. Sensitivity analysis shows that even a relatively low probability of infection following contact between infectious and susceptible individuals may give acceptable control, providing it is counterbalanced by higher survival of both infected and infectious parasite hosts in order to allow the rate of transmission to exceed the threshold required to suppress parasite population growth. The model highlights the need for studies attempting to identify sustainable biocontrol agents to explore the use of pathogens which have a range of the characteristics that contribute to overall pathogenicity, but which are also most compatible with practical application systems.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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".