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Record W1983984276 · doi:10.1081/ada-120002979

Beliefs about the cardiovascular benefits of drinking wine in the adult population of Ontario

2002· article· en· W1983984276 on OpenAlexaffabout
Reginald G. Smart, Alan C. Ogborne

Bibliographic record

VenueThe American Journal of Drug and Alcohol Abuse · 2002
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsWineEnvironmental healthMedicineTelephone surveyPopulationDiseaseHeart diseaseGerontologyHealth benefitsTraditional medicineBusinessFood scienceAdvertising

Abstract

fetched live from OpenAlex

AIMS: to explore beliefs about the cardiovascular benefits of drinking wine in the Ontario population. DESIGN: secondary analysis of data from a provincial survey of adults. PARTICIPANTS: Ontarians aged 18 or older (n = 606) from Ontario living in households and participating in a telephone survey. MEASURES: responses to questions concerning beliefs that wine drinking may reduce the risk of heart disease. Self-reports of age, gender, quantity and frequency of wine drinking, drinking problems, and existence of a diagnosis of heart disease. FINDINGS: a majority of respondents believed that wine drinking reduces heart disease. Almost all (87.6%) said that drinking one or two drinks a day would reduce heart disease. Belief in the health benefits of wine drinking was more common among men, more frequent drinkers, and wine drinkers. CONCLUSIONS: beliefs in the health benefits of wine drinking is common amongst Ontario adults and is consistent with many recommendations by health authorities. The study should be replicated with larger samples in a variety of countries with different drinking patterns.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.046
GPT teacher head0.296
Teacher spread0.250 · 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

Citations10
Published2002
Admission routes2
Has abstractyes

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