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Record W1986639601 · doi:10.1159/000050729

Relation between Average Alcohol Consumption and Disease: An Overview

2001· review· en· W1986639601 on OpenAlexaff
Elisabeth Gutjahr, Gerhard Gmel, Jürgen Rehm

Bibliographic record

VenueEuropean Addiction Research · 2001
Typereview
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersBundesamt für Gesundheit
KeywordsEpidemiologyEnvironmental healthConsumption (sociology)Alcohol consumptionMedicinePublic healthAlcoholPsychologyPathologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To conduct an overview of alcohol-related health consequences and to estimate relative risk for chronic consequences and attributable fractions for acute consequences. METHODS: Identification of alcohol-related consequences was performed by means of reviewing and evaluating large-scale epidemiological studies and reviews on alcohol and health, including epidemiological contributions to major social cost studies. Relative risks and alcohol-attributable fractions were drawn from the international literature and risk estimates were updated, whenever possible, by means of meta-analytical techniques. RESULTS: More than 60 health consequences were identified for which a causal link between alcohol consumption and outcome can be assumed. CONCLUSIONS: Future research on alcohol-related health consequences should focus on standardization of exposure measures and take into consideration both average volume of consumption and patterns of drinking.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.433
GPT teacher head0.490
Teacher spread0.056 · 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 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

Citations190
Published2001
Admission routes1
Has abstractyes

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