Desire and Craving ratings vary significantly for healthy alcohol consumers: Differences in semantic interpretation?
Bibliographic record
Abstract
ABSTRACT Craving is a central concept in alcohol, and other substance, research. Beginning in 1955 the World Health Organization outlined a working definition of the term to be used in research and clinical settings. However, the semantic interpretation of “craving” as a concept is not widely agreed upon. Since the publication of this first craving definition, a handful of studies have been conducted to investigate differences in operational definitions of “craving”, and have demonstrated a lack of agreement between studies and across research subjects. With this background as evidence, our research group investigated, when left to their own semantic understanding of the terms, if regular alcohol consumers would rate craving for alcohol and desire for alcohol in similar ways using related descriptors. Thirty-nine healthy, non-binging regular alcohol consumers were studied across periods of their typical alcohol consumption and imposed alcohol abstinence, collecting ratings of desire and craving for alcohol approximately every two hours across the two experimental periods, and during neutral and alcohol related imagery viewing. Among these non-binging regular drinkers, ratings of desire and craving for alcohol are consistently different while drinking according to a person’s typical routine or abstaining, throughout the day, and when viewing alcohol cue imagery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".