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Record W2995669896 · doi:10.3126/njh.v2i2.26031

Coronary Artery Disease: An emerging Epidemic in Nepal

2003· article· en· W2995669896 on OpenAlexaboutno aff
Arun Maskey, Arun Sayami, Mrigendra Raj Pandey

Bibliographic record

VenueNepalese Heart Journal · 2003
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCoronary artery diseaseDeveloped countryCause of deathDemographyDiseaseDeveloping countryPopulationMortality rateEnvironmental healthSurgeryEconomic growthInternal medicine

Abstract

fetched live from OpenAlex

Cardiovascular diseases (CVD) accounts for approximately 12 millions deaths annually and is the commonest cause of death globally, CVD is also the major contributor to the burden of premature morbidity and mortality and accounted for 85 millions disability adjusted (DALY) life years In 1990. It has been estimated that during the 25 years period from 1965-1990 mortality from coronary artery diseases (CAD) fell by 50% in Australia, Canada, France & US and 60% in Japan and Finland. The identification of major risk factors and effective control of them through population-based strategies of prevention were mainly responsible for this decline. The rise and subsequent decline in CAD epidemic in almost all industrialized countries in the later half of twentieth century has been well documented, but most of the developing countries are experiencing alarming increase of the disease.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.157
GPT teacher head0.495
Teacher spread0.338 · 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.

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
Published2003
Admission routes1
Has abstractyes

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