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Record W2101908116 · doi:10.1136/ebmh.10.3.73

Predictors of symptomatic remission in people with schizophrenia identified

2007· letter· en· W2101908116 on OpenAlexaff
Roger S. McIntyre, Joanna K. Soczynska

Bibliographic record

VenueEvidence-Based Mental Health · 2007
Typeletter
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)PsychiatryPsychologyMedicineClinical psychology

Abstract

fetched live from OpenAlex

Lambert M, Schimmelmann BG, Naber D, et al . Prediction of remission as a combination of symptomatic and functional remission and adequate subjective well-being in 2960 patients with schizophrenia. J Clin Psychiatry 2006;67:1690–7.[OpenUrl][1][PubMed][2] Q What are the predictors of remission in outpatients with schizophrenia? ### ![Graphic][3] Design: Prospective cohort study. ### ![Graphic][4] Setting: European Schizophrenia Outpatient Health Outcomes study, Germany; recruitment January to December 2001. ### ![Graphic][5] Population: 2960 adult outpatients with DSM-IV schizophrenia either switching to or beginning a new antipsychotic (mean age 42 years; 49% male). Exclusions: IQ ⩽70, other DSM-IV schizophrenia spectrum disorders, bipolar I disorder, or psychotic disorder. ### ![Graphic][6] Prognostic factors: Baseline predictors: age; gender; illness duration; symptoms (Clinical Global Impressions-Severity of Illness (CGI)-Schizophrenia scale overall severity score subscale scores). Functional predictors included occupational status, independent living and subjective wellbeing (Subjective Wellbeing Under Neuroleptic Treatment Scale (SWN-K)). Antipsychotic treatment factors included first antipsychotic, neurological side effects, and … [1]: {openurl}?query=rft.jtitle%253DJ%2BClin%2BPsychiatry%26rft.volume%253D67%26rft.spage%253D1690%26rft_id%253Dinfo%253Apmid%252F17196047%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=17196047&link_type=MED&atom=%2Febmental%2F10%2F3%2F73.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif [6]: /embed/inline-graphic-4.gif

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)0.003
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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.332
Teacher spread0.296 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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