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Record W1967473350 · doi:10.2190/pm.41.3.c

Schizophrenia: Medical Illness, Mortality, and Aging

2011· review· en· W1967473350 on OpenAlexaff
David Casey, Mercedes M. Rodriguez, Colleen J. Northcott, Garry M. Vickar, Lina Shihabuddin

Bibliographic record

VenueThe International Journal of Psychiatry in Medicine · 2011
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Context (archaeology)PsychiatryMedicineDiseaseQuality of life (healthcare)MEDLINEPsychosisLife spanGerontology

Abstract

fetched live from OpenAlex

OBJECTIVE: Schizophrenia is a devastating and common psychiatric disorder which is associated with a high degree of medical morbidity and reduced life span in addition to psychosis. In this article, these problems will be discussed in the context of schizophrenia and aging. METHOD: The recent literature was reviewed using Pubmed, Medline, and Google scholar with the search terms "schizophrenia, aging, medical problems." RESULTS: Schizophrenia is associated with significant medical morbidity and mortality. Diabètes and cardiovascular disease, along with smoking and obesity, are over-represented and contribute to reduced quality of life and life span. Schizophrenics often receive poor medical care. CONCLUSIONS: The impacts of schizophrenia on physical health and successful aging have been underestimated. Psychiatrists and primary care physicians need to address the overlapping medical and psychiatric aspects of the disorder while the medical care system for these patients requires a much higher degree of coordination than is currently available.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.083
GPT teacher head0.426
Teacher spread0.343 · 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
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

Citations50
Published2011
Admission routes1
Has abstractyes

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