Review: Varenicline is better than placebo or bupropion, but not clearly different from the nicotine patch, for smoking abstinence
Bibliographic record
Abstract
ACP Journal Club19 April 2011Review: Varenicline is better than placebo or bupropion, but not clearly different from the nicotine patch, for smoking abstinenceJames Brophy, MD, PhDJames Brophy, MD, PhDMcGill University, Montreal, Quebec, Canada (J.B.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-154-8-201104190-02004 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Source CitationCahill K, Stead LF, Lancaster T. Nicotine receptor partial agonists for smoking cessation. Cochrane Database Syst Rev. 2011;(2):CD006103. https://pubmed.ncbi.nlm.nih.gov/21328282Clinical Impact RatingsGIM/FP/GP: Pulmonology: Author, Article, and Disclosure InformationAffiliations: McGill University, Montreal, Quebec, Canada (J.B.)This article was published at Annals.org on 5 April 2011. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics 19 April 2011Volume 154, Issue 8Page: JC4-4KeywordsAdverse eventsInsomniaLung and intrathoracic tumorsNauseaNicotineResearch fundingSafetySafety studies ePublished: 19 April 2011 Issue Published: 19 April 2011 Copyright & PermissionsCopyright © 2011 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".