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Record W7099587540

Health Unit Encourages You to Rethink Your Drinking

2014· article· en· W7099587540 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGraphene and Nanomaterials Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHarmLimitingUnit of alcoholAlcohol consumptionConsumption (sociology)Unit (ring theory)Occupational safety and healthSuicide prevention
DOInot available

Abstract

fetched live from OpenAlex

For the first time ever, Canada has one national set of low-risk alcohol drinking guidelines. These guidelines, intended for Canadians of legal drinking age who choose to drink alcohol, aim to provide consistent information across the country to help Canadians moderate their alcohol consumption and make informed choices. The new guidelines outline standard drink sizes, limits for men and women, discuss when the limit is zero, and provide healthy alternatives and tips to decrease health risks. When it comes to alcohol, drinking is a personal choice, and the majority of people drink responsibly. We're not asking you to stop drinking … instead we want you to Rethink Your Drinking, and gradually reduce the amount of alcohol you consume as part of a healthy lifestyle. If you choose to drink, these guidelines can help you decide when, where, why and how. We all have reasons to celebrate. Celebrations and special events are times when the guidelines can help you make decisions about drinking alcohol – Rethinking your Drinking! Knowing your limits and standard drink sizes, can help you make the right decisions for you. You can reduce your risk of harm or injury, by limiting alcoholic drinks to no more than 3 drinks for women or 4 drinks for men on special occasions. If you host a party and alcohol is served,

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.304

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.018
GPT teacher head0.254
Teacher spread0.237 · 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 designNot applicable
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

Citations0
Published2014
Admission routes1
Has abstractyes

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Same topicGraphene and Nanomaterials ApplicationsFrench-language works237,207