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Record W4391678523 · doi:10.1016/j.heliyon.2024.e26118

Tick-borne viruses and their risk to public health in the Caribbean: Spotlight on bats as reservoirs in Cuba

2024· article· en· W4391678523 on OpenAlexaff
Maritza Pupo Antúnez, José Carlos Marín Montesinos, Alexandra Corduneanu, Dasiel Obregón, Sara Moutailler, Alejandro Cabezas‐Cruz

Bibliographic record

VenueHeliyon · 2024
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPublic healthVirologyCaribbean regionTickGeographyBiologyEnvironmental healthLatin AmericansMedicinePolitical sciencePathology

Abstract

fetched live from OpenAlex

In recent decades, tick-borne diseases (TBDs) have surged and expanded globally due to factors like changes in human activities, land use patterns, and climate change, and it have been associated with the emergence of zoonotic diseases. Cuba faces the impact of ticks on human health and the economy. Although Cuba has studied TBDs extensively for the past 50 years, focus on tick-borne viral pathogens affecting humans remains scant. Despite TBDs not currently being a major health concern in Cuba, factors like inadequate clinician awareness, climate conditions, global tick emergence, and evidence of zoonotic pathogens in ticks underscore the importance of enhanced TBD surveillance in the country. Here we revised the available information on ticks as vectors of pathogenic viruses to humans, spotlighting bats as potential reservoirs of tick-borne viruses (TBVs). Ticks on bats have gained interest as potential reservoirs of pathogenic viruses to humans in Cuba and worldwide. Understanding their role in maintaining viruses and their potential transmission to humans is crucial for the implementation of surveillance and control programs to reduce the risk of tick-borne viral diseases and public health management.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.050
GPT teacher head0.338
Teacher spread0.287 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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