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Record W3013205941 · doi:10.3390/proceedings2020043004

Proceedings of the 10th Alcohol Hangover Research Group Meeting in Utrecht, The Netherlands

2020· article· en· W3013205941 on OpenAlexaff
Agnese Merlo, Zack Abbott, Chris Alford, Stephanie Balikji, Gillian Bruce, Craig Gunn, Jacqueline M. Iversen, Jim Iversen, Sean Johnson, L. Darren Kruisselbrink, Aurora J.A.E. van de Loo, Marlou Mackus, Chantal Terpstra, Ann‐Kathrin Stock, Joris C. Verster

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsAcadia University
Fundersnot available
KeywordsCognitionPsychologyAbsenteeismAlcohol consumptionAlcoholInjury preventionAlcohol intoxicationHuman factors and ergonomicsOccupational safety and healthPoison controlEnvironmental healthMedicineClinical psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

The hangover is the most commonly reported negative consequence of alcohol use with several studies reporting the detrimental consequences of hangover on health, economy, and society. Research has emphasized the socioeconomic consequences of experiencing these physical and psychological symptoms in relation to absenteeism, increased risk of having accidents and injuries, and impairment of daily activities, such as job performance and driving a car. During the 10th Alcohol Hangover Research Group meeting, held on 29 April 2018, in Utrecht, The Netherlands, aspects of alcohol hangover were presented with regards to determinants, biological and cognitive consequences and potential treatments. Precursory and posterior factors influencing alcohol hangover, including biological, psychological, behavioral, metabolic aspects, cognitive functioning, and the role of the immune system in the development of alcohol hangover, were presented. In addition, potential preventive measures and treatments of alcohol hangover to reduce the adverse consequences of alcohol consumption and hangover symptoms were discussed. One study revealed that an average of 24% of social and heavy drinkers claimed not to experience hangover symptoms across time. Another study showed that food intake (either healthy or junk food) had no significant impact on next-day hangover severity. Research examining cognitive and psychomotor functioning during hangover revealed impairments in collective problem solving and response inhibition, but not attentional bias towards alcohol-related cues. The alcohol hangover state further significantly impaired driving performance, even for a short commute to work. With regard to the pathology of the alcohol hangover, research was presented that demonstrated increases in saliva cytokine concentrations confirming drinking alcohol and the hangover phase are both associated with an immune response. Other presentations discussed that scientific literature shows that there are no effective hangover treatments available yet. However, although promising, new hangover treatments are currently in development. Taken together, at the 10th Alcohol Hangover Research Group meeting, a comprehensive overview of the causes, consequences, and potential treatments of the alcohol hangover was presented.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.124
GPT teacher head0.367
Teacher spread0.244 · 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 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

Citations4
Published2020
Admission routes1
Has abstractyes

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