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Record W2018350887 · doi:10.1002/hup.866

Relationship between the cardiac response to acute intoxication and alcohol‐induced subjective effects throughout the blood alcohol concentration curve

2007· article· en· W2018350887 on OpenAlexafffund
Caroline Brunelle, Sean P. Barrett, Robert O. Pihl

Bibliographic record

VenueHuman Psychopharmacology Clinical and Experimental · 2007
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsDalhousie UniversityMcGill UniversityUniversity of New Brunswick
FundersCanadian Institutes of Health Research
KeywordsAlcoholStimulantSedativeBlood alcoholEthanolMedicineArea under the curveIngestionAnesthesiaInternal medicinePoison controlInjury preventionChemistryBiochemistryEmergency medicine

Abstract

fetched live from OpenAlex

RATIONALE: There is evidence to suggest that individual differences in the subjective response to alcohol exist and exaggerated cardiac response to alcohol has been suggested to be a marker of increased sensitivity to the stimulant properties of alcohol. OBJECTIVES: The present investigation examines the relationship between cardiac reactivity to alcohol measured on the ascending limb of the Blood Alcohol Concentration (BAC) curve and the subjective stimulant and sedative effects of alcohol throughout the BAC curve. METHODS: The stimulant and sedative effects of alcohol anticipatory to alcohol and during the ascending and descending limbs of the BAC curve were evaluated using the Biphasic Alcohol Effects Scale in 39 male social drinkers. RESULTS: Cardiac response to ethanol measured on the ascending limb of the BAC curve was positively correlated with intoxicated stimulant effects at numerous time points during the ascending and descending limbs of the BAC curve (ps < 0.01). No associations were found between cardiac change following alcohol and alcohol-related sedative effects at any time point. CONCLUSIONS: Objective and subjective reports of stimulation post-alcohol ingestion may increase risk for problematic 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 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)0.003
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 score0.189
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.162
GPT teacher head0.541
Teacher spread0.379 · 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

Citations47
Published2007
Admission routes2
Has abstractyes

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