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Record W2050555717 · doi:10.1016/j.gheart.2012.01.001

Burden of Cardio- and Cerebro-vascular Diseases and the Conventional Risk Factors in South Asian Population

2012· article· en· W2050555717 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGlobal Heart · 2012
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsSouth Health CampusUniversity of Calgary
Fundersnot available
KeywordsMedicineChecklistObservational studyGlobal healthEpidemiologySystematic reviewPopulationPublic healthFamily medicineEnvironmental healthMEDLINEPathologyPolitical sciencePsychology

Abstract

fetched live from OpenAlex

Similar to most populations, South Asian countries are also witnessing the dramatic transitions in health during the last few decades with the major causes of adverse health shifting from a predominance of nutritional deficiencies and infectious diseases to chronic diseases such as cardio and cerebrovascular disease (CVD). We summarized the available information of the burden of CVD and risk factors in the South Asian populations. The prevalence of conventional cardiovascular has been increasing among all South Asian populations. Extensive urbanization, shift in dietary pattern and sedentary daily life style is contributing towards the worsening of the CVD risk factor scenario. The burdens of the chronic cardiovascular risk factors are much prevalent in the South Asian populations. These are also rising alarmingly which ought to influence the already existed heavy CVD burden. Similar to the rest of the world, management for the conventional cardiovascular risk factors is very important for the prevention of CVD in South Asia.

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.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.237
Teacher spread0.230 · 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