Peculiarities of the Epidemic Situation on West Nile Fever in the Territory of the Russian Federation in 2018 and Forecast of its Development in 2019
Bibliographic record
Abstract
The epidemic rise in the incidence of West Nile fever (WNF) in the season of 2018 was observed in the countries of the European Union (EU) and bordering states and exceeded the values of all previously recorded epidemic rises of 2010–2012. An increase in the incidence rate was registered in the USA and Canada, however, it did not exceed the indicators of epidemic rises of 2007–2012. In the territory of the Russian Federation, the WNF epidemiological process became more intense mainly in the territory of the Southern and North Caucasian Federal Districts. In general, in Russia, the incidence rates were 2 times lower than the average annual rates, but significantly exceeded those of 2017. The epidemic process had a number of peculiarities in the seasonality, the structure of morbidity and the clinical manifestation of WNF. Genotyping of the isolated WNV RNA fragments from clinical and biological material showed that I, II and IV West Nile virus genotypes were circulating in the European part of Russia. Forecast of epidemic situation development in 2019 reveals further increase in the incidence and does not exclude the possibility of a significant localincrease of WNF incidence in certain regions of Russia.
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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 | 0.000 |
| 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) | 0.000 | 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".