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Record W2114222653 · doi:10.2174/1874473711003020116

The Alcohol Hangover Research Group Consensus Statement on Best Practice in Alcohol Hangover Research

2010· article· en· W2114222653 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Drug Abuse Reviews · 2010
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsAcadia University
FundersNational Institute on Alcohol Abuse and Alcoholism
KeywordsAlcohol consumptionAlcoholAbsenteeismHuman factors and ergonomicsEnvironmental healthAlcohol intakeOccupational safety and healthInjury preventionAlcohol intoxicationPoison controlMedicinePsychologySuicide preventionSocial psychology

Abstract

fetched live from OpenAlex

Alcohol-induced hangover, defined by a series of symptoms, is the most commonly reported consequence of excessive alcohol consumption. Alcohol hangovers contribute to workplace absenteeism, impaired job performance, reduced productivity, poor academic achievement, and may compromise potentially dangerous daily activities such as driving a car or operating heavy machinery. These socioeconomic consequences and health risks of alcohol hangover are much higher when compared to various common diseases and other health risk factors. Nevertheless, unlike alcohol intoxication the hangover has received very little scientific attention and studies have often yielded inconclusive results. Systematic research is important to increase our knowledge on alcohol hangover and its consequences. This consensus paper of the Alcohol Hangover Research Group discusses methodological issues that should be taken into account when performing future alcohol hangover research. Future research should aim to (1) further determine the pathology of alcohol hangover, (2) examine the role of genetics, (3) determine the economic costs of alcohol hangover, (4) examine sex and age differences, (5) develop common research tools and methodologies to study hangover effects, (6) focus on factor that aggravate hangover severity (e.g., congeners), and (7) develop effective hangover remedies.

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.

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)0.070
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.596
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0700.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.012
Insufficient payload (model declined to judge)0.0010.017

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 head0.436
GPT teacher head0.631
Teacher spread0.194 · 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