Safety and Efficacy of GABAergic Medications for Treating Alcoholism
Bibliographic record
Abstract
This article highlights the proceedings of a symposium presented at the 27th Annual Scientific Meeting of the Research Society on Alcoholism in Vancouver, British Columbia, Canada, June 29, 2004. The organizers and co-chairs were Bankole A. Johnson, MD, PhD, and Robert M. Swift, MD, PhD. The presentations included (1) Introduction, by Bankole A. Johnson; (2) Safety, Tolerability, and Efficacy of gamma-Hydroxybutyric Acid and Baclofen in the Treatment of Alcohol Addiction, by Giovanni Addolorato; (3) Safety of Gabapentin in Treating Alcoholism, by Hugh Myrick; (4) New Data on the Safety and Effectiveness of Topiramate in the Treatment of Alcohol Dependence, by Bankole A. Johnson; (5) Evaluating the Risk of Benzodiazepine Prescription to Alcohol-Dependent Individuals, by Domenic A. Ciraulo; and (6) Safety and Efficacy of GABAergic Agents in Treating Alcoholics: Discussion, by Robert M. Swift.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".