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Review: Varenicline is better than placebo or bupropion, but not clearly different from the nicotine patch, for smoking abstinence

2011· letter· en· W1997886537 on OpenAlexaffabout
James M. Brophy

Bibliographic record

VenueAnnals of Internal Medicine · 2011
Typeletter
Languageen
FieldMedicine
TopicRespiratory and Cough-Related Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineVareniclineBupropionNicotine patchSmoking cessationAbstinencePlaceboNicotineInternal medicineFamily medicinePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

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 ...

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.139
GPT teacher head0.376
Teacher spread0.237 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2011
Admission routes2
Has abstractyes

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