Contagious Bovine and Caprine Pleuropneumonia: a research community’s recommendations for the development of better vaccines
Bibliographic record
Abstract
Abstract Contagious bovine pleuropneumonia (CBPP) and contagious caprine pleuropneumonia (CCPP) are major infectious diseases of ruminants caused by mycoplasmas in Africa and Asia. In contrast with the limited pathology in the respiratory tract of humans infected with mycoplasmas, CBPP and CCPP are devastating diseases associated with high morbidity and mortality. Beyond their obvious impact on animal health, CBPP and CCPP negatively impact the livelihood and wellbeing of a substantial proportion of livestock-dependent people affecting their culture, economy, trade and nutrition. The causative agents of CBPP and CCPP are Mycoplasma mycoides subspecies mycoides and Mycoplasma capricolum subspecies capripneumoniae , respectively, which have been eradicated in most of the developed world. The current vaccines used for disease control consist of a live attenuated CBPP vaccine and a bacterin vaccine for CCPP, which were developed in the 1960s and 1980s, respectively. Both of these vaccines have many limitations, so better vaccines are urgently needed to improve disease control. In this article the research community prioritized biomedical research needs related to challenge models, rational vaccine design and protective immune responses. Therefore, we scrutinized the current vaccines as well as the challenge-, pathogenicity- and immunity models. We highlight research gaps and provide recommendations towards developing safer and more efficacious vaccines against CBPP and CCPP.
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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 | 0.029 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".