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Record W1999200912 · doi:10.1159/000284813

Clinical Features of Situational and Nonsituational Major Depression

2010· article· en· W1999200912 on OpenAlexaff
Russel T. Joffe, Anthony Levitt, Michael Bagby, Joseph J. Regan

Bibliographic record

VenuePsychopathology · 2010
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsSt. Michael's HospitalCentre for Movement DisordersUniversity of Toronto
Fundersnot available
KeywordsSituational ethicsDepression (economics)PsychologyPersonalityClinical psychologyPsychiatryMajor depressive disorderAntidepressantAnxietySocial psychologyCognition

Abstract

fetched live from OpenAlex

Clinical lore has long supported the subtype of situational or reactive depression. To date, however, there has been limited empirical research support for this subtype of major depression. We examined demographic, clinical and personality features of situational and nonsituational depression in 89 outpatients with unipolar nonpsychotic major depressive disorder. Situational depressives had a less recurrent course of illness and appeared to respond more completely to the antidepressant used for their current episode. Demographic and personality measures did not distinguish situational and nonsituational depression.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.482
Teacher spread0.430 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations10
Published2010
Admission routes1
Has abstractyes

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