MétaCan
Menu
Back to cohort
Record W1999259854 · doi:10.1517/14656566.6.5.819

An evaluation of paroxetine in generalised social anxiety disorder

2005· review· en· W1999259854 on OpenAlexaffabout
Michael Van Ameringen, Catherine Mancini, Beth Patterson, Mark Bennett

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2005
Typereview
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsMcMaster UniversityHamilton Health SciencesMcMaster University Medical Centre
Fundersnot available
KeywordsParoxetineSocial anxietyAnxietyPsychiatryMedicinePharmacotherapyAnxiety disorderPlaceboClinical psychologyPsychologyAntidepressantAlternative medicine

Abstract

fetched live from OpenAlex

It is estimated that social anxiety disorder affects approximately 13.3% individuals within the community at some point in their lifetime and is associated with significant functional impairment. A variety of drug groups have demonstrated efficacy in treating social anxiety disorder, including selective serotonin reuptake inhibitors (SSRIs). Paroxetine is an SSRI approved by the FDA and Health Canada for the treatment of a variety of psychiatric conditions. Paroxetine has been the most studied agent in social anxiety disorder and has been shown to be effective in short-term, fixed- and flexible-dose placebo-controlled trials, as well as in long-term treatment. The pharmacotherapy of social phobia will be reviewed, with a special focus on investigations with paroxetine.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.222
GPT teacher head0.553
Teacher spread0.331 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations3
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueExpert Opinion on PharmacotherapySame topicAnxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesFrench-language works237,207