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Record W2079060392 · doi:10.1371/journal.pone.0083539

Clozapine Prescribing in a Canadian Outpatient Population

2013· article· en· W2079060392 on OpenAlexaffabout
Silvia Alessi‐Severini, Josée-Anne Le Dorze, David H. Nguyen, Patricia L. Honcharik, Michael Eleff

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsHealth Sciences CentreUniversity of Manitoba
Fundersnot available
KeywordsClozapineMedicineSchizophrenia (object-oriented programming)AntipsychoticPopulationRetrospective cohort studyPediatricsDemographicsPsychiatryInternal medicineDemography

Abstract

fetched live from OpenAlex

OBJECTIVE: Description of demographics of an outpatient population of clozapine users. METHODS: Retrospective chart review study of an urban population diagnosed with schizophrenia. Assessment of therapeutic histories in relation to clinical practice guidelines. RESULTS: Seventy-seven of the 467 patients were on clozapine therapy. Average patients' age was 39.4 ± 11.8 years) and 68% were males. The majority of patients (68%) had tried 3 or more antipsychotics before switching to clozapine, 21% had tried two and 11% had tried one. Median length of therapy prior to clozapine initiation was 8.9 years in males and 7.7 years in females. CONCLUSION: Until 2010, the use of clozapine was often delayed and more than 2 antipsychotic medications were tried for relatively long periods of time before patients were switched to this effective agent.

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)0.001
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 score0.086
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.060
GPT teacher head0.260
Teacher spread0.200 · 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

Citations28
Published2013
Admission routes2
Has abstractyes

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