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Record W4312211120 · doi:10.1093/jtm/taac139

Dengue outbreak amongst travellers returning from Cuba—GeoSentinel surveillance network, January–September 2022

2022· article· en· W4312211120 on OpenAlexaff
Marta Díaz‐Menéndez, Kristina M Angelo, Rosa de Miguel Buckley, Emmanuel Bottieau, Ralph Huits, Martin P. Grobusch, Federico Gobbi, Hilmir Ásgeirsson, Alexandre Duvignaud, Francesca Norman, Émilie Javelle, Loïc Epelboin, Camilla Rothe, François Chappuis, Gabriela E. Martínez, Corneliu Petru Popescu, Daniel Camprubí, Israel Molina, Silvia Odolini, Sapha Barkati, Susan Kuhn, Stephen Vaughan, Anne Marie McCarthy, Mar Lago, Michael Libman, Davidson H. Hamer

Bibliographic record

VenueJournal of Travel Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsOttawa HospitalAlberta Children's HospitalMcGill University Health Centre
FundersNational Institutes of HealthCenters for Disease Control and PreventionInternational Society of Travel Medicine
KeywordsOutbreakDengue feverMedicineDengue virusVirologyTravel medicineEnvironmental health

Abstract

fetched live from OpenAlex

Increasing numbers of travellers returning from Cuba with dengue virus infection were reported to the GeoSentinel Network from June to September 2022, reflecting an ongoing local outbreak. This report demonstrates the importance of travellers as sentinels of arboviral outbreaks and highlights the need for early identification of travel-related dengue.

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)0.001
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 score0.331
Threshold uncertainty score0.658

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.287
Teacher spread0.264 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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