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Record W4212766454 · doi:10.7759/cureus.22300

The Risk of Cardiovascular Disease Among Immigrants in Canada

2022· review· en· W4212766454 on OpenAlexaboutno aff
Sneha Annie Sebastian, Chaithanya Avanthika, Sharan Jhaveri, Keila G Carrera, Génesis Camacho-Leon, Ramya Balasubramanian

Bibliographic record

VenueCureus · 2022
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineImmigrationEthnic groupDiseaseIncidence (geometry)Diabetes mellitusEnvironmental healthDemographyGerontologyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. The global surge in migration to high-income countries, especially Canada, highlights the importance of studies evaluating the risk factors and the disparities in the rate of incidence of CVD among immigrants. Canada is home to a diverse group of immigrants, each presenting with a risk profile that is unique to their ethnicity and country of birth. A variety of cardiac risk factors, such as dietary habits, physical activity, smoking, cultural traditions as well as preponderance to certain diseases like type II diabetes mellitus, hypertension, and high lipid levels act in concert and impact CVD risk and overall incidence. This narrative review focuses on CVD risks and how it is related to the immigration status among various ethnic groups in Canada.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.784
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.281
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2022
Admission routes1
Has abstractyes

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