Monitoring the epizoetic situation on mixed infectious diseases in bees in Northern Eastern region of Ukraine
Bibliographic record
Abstract
In most countries of the world, infectious diseases of bees are an important problem for beekeeping, as they lead to a decrease and decrease in the number of bee colonies, a negative impact on the environment, a decrease in the yield of entomophilic crops and the overall productivity of the industry as a whole. According to data from statistical reporting and scientific publications, American and European flocks, ascospheros are registered in apiaries almost all over the world: in Western and Eastern Europe, North and Central America, Canada, Australia and New Zealand, Africa, in the CIS countries. The change in the epizootic situation in bee-keeping is associated with the widespread spread of the varioise invasion, which causes a steady increase in the incidence of bee infestation by infectious diseases, so the effect of this invasion on the intensity of the epizootic process requires constant monitoring research. Among the topical tasks of the veterinary support of the beekeeping industry in the improvement of the system of antiepizootic measures, the differential diagnosis of infectious diseases of the breeding pedigree in the mixed forms of their manifestation was very important. The difficulty in making the correct diagnosis in mixed forms of the course of infectious diseases leads to inadequate and untimely conduct of treatment and preventive measures, and as a consequence, to the weakening and death of bees. In this regard, the development of an epizootiological monitoring system aimed at recording and evaluating changes in the epizootic state of apiaries, the identification of sources and reservoirs of pathogens, the motive forces of the epizootic process and the forms of the disease, and the organization of a system of effective preventive, medical and veterinary-sanitary measures on the apiaries. In the period of economic transformations in the agrarian-industrial complex there was a lack of breeding of beekeeping farms and apiaries, a system of management of the industry and a form of ownership changed, all this created a qualitatively new environment of the bee colony and contributed to the evolution of the epizootic process in infectious diseases – the development of mixed infections. In connection with this, there was a need to improve the system of epidemiological surveillance in beekeepers and to introduce a more effective comprehensive system of measures for the prevention and control of infectious diseases of the breeding bee, in particular, American rot, varrosis and other contagious diseases of bees.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".