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Record W4412936953 · doi:10.24875/acm.24000239

Inmunización y enfermedad cardiovascular en América Latina. El estudio CorVacc: fundamento y diseño

2025· article· es· W4412936953 on OpenAlexaff
Fernando Wyss, Ricardo López Santi, Daniel Piskorz, Shyla Gupta, Ana G Múnera, Pilar López-Santi, Gonzalo Piskorz, Vladimir Ulluauri, Juan E. Gomez, Mildren Del Sueldo, Claudia Almonte, Osiris Valdez, Carlos I. Ponte‐Negretti, Iván Romero-Rivera, Adriana Puente-Barragán, Raúl Villar, Edmundo Jordan, Wistremundo Dones, Daniel Quezada, Gonzalo L. Pérez, Adrián Baranchuk

Bibliographic record

VenueArchivos de cardiología de México · 2025
Typearticle
Languagees
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsKingston Health Sciences CentreUniversity of Ottawa
FundersSanofi
KeywordsHumanitiesMedicineArt

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the rates of vaccination against influenza and pneumococcal disease in the general population of the Americas, both healthy and sick, and to analyze the factors influencing these rates. METHODS: The Inter-American Vaccination Registry of Influenza and Pneumococcus, (CorVacc Study) is a cross-sectional survey of the general population that will be enacted in 19 Latin American countries. A total of 34 questions will be given to consecutive patients aged 18 years or older through an online survey. RESULTS: The data will be analyzed by country and region according to seven clusters: demographics, socioeconomic and educational level, cardiometabolic profile, cardiovascular interventions, medical follow-up and treatments, and COVID-19 vaccination status. The study will be conducted by the Prevention Council of the Inter-American Society of Cardiology. CONCLUSIONS: This study will provide insight into the impact of influenza and pneumococcus vaccinations in Latin American populations and the barriers preventing the immunization targets from being actualized. Hopefully, this will help to facilitate the development of targeted and focused health prevention strategies.

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)0.004
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.036
GPT teacher head0.366
Teacher spread0.330 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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