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Increased risk of chikungunya infection in travellers to Thailand during ongoing outbreak in tourist areas: cases imported to Europe and the Middle East, early 2019

2019· article· en· W2922479263 on OpenAlexfundno aff
Émilie Javelle, Simin-Aysel Florescu, Hilmir Ásgeirsson, Shilan Jmor, Gilles Éperon, Eyal Leshem, Johannes Blum, Israel Molina, Vanessa Field, Nancy Pietroski, Carole Eldin, Victoria Johnston, Corneliu Petru Popescu, Davidson H. Hamer, Philippe Gautret

Bibliographic record

VenueEurosurveillance · 2019
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
FundersInternational Society of Travel MedicineUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si InovariiColegiul Consultativ pentru Cercetare-Dezvoltare şi InovarePublic Health AgencyPublic Health Agency of CanadaCenters for Disease Control and Prevention
KeywordsChikungunyaOutbreakTourismTransmission (telecommunications)GeographySocioeconomicsMiddle EastAlphavirus infectionMedicineEnvironmental healthVirology

Abstract

fetched live from OpenAlex

We report nine travellers with confirmed chikungunya virus infection, returning from tourist areas of Thailand to Sweden, Switzerland, the United Kingdom, Romania, Israel and France, diagnosed in January and February 2019. These sentinel tourists support the intensification of chikungunya virus circulation in Thailand and highlight the potential for importation to areas at risk of local transmission.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2019
Admission routes1
Has abstractyes

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