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Consommation à faible risque d’alcool : le moins, le mieux ?

2023· review· fr· W4379599411 on OpenAlexaboutno aff
Jennifer Muradbegovic, Thierry Favrod-Coune

Bibliographic record

VenueRevue Médicale Suisse · 2023
Typereview
Languagefr
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsAlcohol consumptionHumanitiesPolitical sciencePhilosophyAlcoholChemistry

Abstract

fetched live from OpenAlex

The limits for low-risk drinking have been a topic of debate among expert groups for several years, with variations observed across countries. In Canada, the recently established low-risk drinking limits are notable for their unprecedented and historically low threshold, allowing for 2 standard drinks (of 13.6 grams) or less per week. In comparison, Switzerland has set the limits at 5 standard drinks (of 10 g) per week for women and 10 for men. In this article, we will conduct a non-systematic review of the literature on the risks and benefits associated with alcohol consumption, followed by a comparison of the evolution of various consumption limits established over the past 30 years. Lastly, we will provide a critical perspective to support individuals in making informed decisions about their alcohol consumption.

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)0.004
metaresearch head score (Gemma)0.014
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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.079
GPT teacher head0.334
Teacher spread0.256 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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