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Epidemic Situation on West-Nile Fever in 2014 in the Territory of the Russian Federation and Around the World, and Prognosis for its Development in 2015

2015· article· en· W2596863160 on OpenAlexaboutno aff
E. V. Putintseva, V. P. Smelyansky, V. A. Pak, Н. В. Бородай, К. В. Жуков, V. V. Manankov, N. I. Pogasiy, Г. А. Ткаченко, L. V. Lemasova, M. L. Ledeneva, Н. Д. Пакскина, Д. В. Викторов, В. А. Антонов

Bibliographic record

VenueProblems of Particularly Dangerous Infections · 2015
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsnot available
Fundersnot available
KeywordsRussian federationWest Nile virusGeographyVirologyMediterranean climateSocioeconomicsDemographyVirusBiologyArchaeologySociology

Abstract

fetched live from OpenAlex

West-Nile fever epidemic season lasted since May to September inclusively in 2014 in Russia. It was marked by the low morbidity intensity, which manifested itself in the old-established foci only. In total reported were 27 cases of West-Nile fever infection in 8 constituent entities of the Russian Federation. Decrease in epidemic process intensity was observed in other parts of the world too: the USA, Canada, European and Mediterranean countries. Sustained circulation of WNF virus of the second genotype in the territory of the Russian Federation (the Volgograd Region) was verified using sequencing of the fragments of the viral RNA genome locuses 5’UTR-protC, ProtE, NS3 obtained from clinical material and ambient environment objects.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.312
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2015
Admission routes1
Has abstractyes

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