MétaCan
Menu
Back to cohort
Record W1968189925 · doi:10.1159/000050732

Average Volume of Alcohol Consumption, Drinking Patterns and Related Burden of Mortality in Young People in Established Market Economies of Europe

2001· article· en· W1968189925 on OpenAlexaff
Jürgen Rehm, Gerhard Gmel, Robin Room, Ulrich Frick

Bibliographic record

VenueEuropean Addiction Research · 2001
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersBundesamt für GesundheitWorld Health Organization
KeywordsConsumption (sociology)Alcohol consumptionAlcoholEnvironmental healthDemographyMedicineVolume (thermodynamics)Injury preventionSuicide preventionHuman factors and ergonomicsPoison controlGeographySociologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the burden of mortality in young people (age 15-29) in established market economies in Europe in 1999, which is attributable to alcohol consumption. Two dimensions of alcohol consumption were considered: average volume of consumption, and patterns of drinking. METHODS: Mortality data were obtained from the WHO EIP data bank, average volume data from the WHO global databank on alcohol, pattern of drinking data from a questionnaire sent out to experts, from the published literature and from the WHO global databank. Methods are explained and discussed in detail in two other contributions to this volume. RESULTS: More than 8,000 deaths of people aged 15-29 in Europe in 1999 were attributable to alcohol. Young males show a higher proportion of alcohol-attributable deaths (12.8%) than females (8.3%). Both average volume and patterns of drinking contribute to alcohol-related death. CONCLUSIONS: Alcohol-related deaths constitute a considerable burden in young people in Europe.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.325
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), 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

Citations38
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Addiction ResearchSame topicSubstance Abuse Treatment and OutcomesFrench-language works237,207