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Record W2009045165 · doi:10.1080/13651500701419644

Still no evidence that benzodiazepines cause depression

2008· article· en· W2009045165 on OpenAlexaff
Scott B. Patten

Bibliographic record

VenueInternational Journal of Psychiatry in Clinical Practice · 2008
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDepression (economics)MoodPsychiatryPsychologyMood disordersDrugBipolar disorderMedicineAnxiety

Abstract

fetched live from OpenAlex

A large number of drugs have been implicated in causing depression by case reports and case series. For a few specific drugs, the association has subsequently been confirmed by appropriately designed studies. In other instances, a lack of substantiating evidence has lead to a gradual disappearance of concern about a potential association. The benzodiazepines represent a deviation from this pattern: they are widely believed to cause depression, but there is a lack of evidence to substantiate this claim. In DSM-IV, there is a category of mood disorder for drug-induced depression (substance-induced mood disorder), and the text of the manual specifically refers to benzodiazepines as a potential cause. Despite the apparently entrenched nature of this belief, there continues to be a lack of credible evidence that benzodiazepines can cause depression as a side effect.

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)0.006
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.041
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0170.004

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 head0.182
GPT teacher head0.507
Teacher spread0.325 · 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 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

Citations3
Published2008
Admission routes1
Has abstractyes

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