Peculiarities of Epidemiological Situation on the West Nile Fever in 2012 in the Territory of the Russian Federation
Bibliographic record
Abstract
During the epidemic season of 2012 453 cases of West Nile fever (WNF) were registered in the territory of the 21 constituent entities of the Russian Federation. Epidemic process is spreading itself towards the northern regions of Russia. The presence of markers of West Nile fever virus in carriers and vectors of the disease as well as acquired immunity among the population against the West Nile virus (WNV) have been identified in the territory of 53 constituent entities of the Russian Federation. The epidemic process is characterized by a number of peculiarities concerning both its epidemiological and clinical aspects. With the intensification of diagnostic works among the patients with clinical symptomatology similar to WNF, first and foremost in the territories where WNV markers have been detected, prognosticated is the registration of WNF incidence among the population extending over a large area of the Russian Federation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".