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Record W2018381577 · doi:10.3371/csrp.segu.030113

Selective Review of Age-Related Needs of Women with Schizophrenia

2013· review· en· W2018381577 on OpenAlexaff
Mary V. Seeman, Rina Gupta

Bibliographic record

VenueClinical Schizophrenia & Related Psychoses · 2013
Typereview
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychological interventionSchizophrenia (object-oriented programming)PsychologyCategorizationPsychiatryClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Recognizing that needs differ between men and women with schizophrenia and that they vary over time, this review attempts to categorize the needs that are relevant to younger and to older women. METHOD: This is a selective literature review focusing on topic areas the two authors determined to be most germane to women with schizophrenia. Articles were selected on the basis of currency, comprehensiveness, and study design. Particular attention was paid to the voices of the women themselves. RESULTS: There is considerable overlap between the needs of younger and older women with schizophrenia, but as a general rule, younger women require preventive strategies to stop the escalation of illness while older women require recovery interventions to regain lost hopes and abilities. CONCLUSIONS: There is clinical utility in cataloguing the needs of younger and older women with schizophrenia and conceptualizing interventions according to gender and age rather than viewing needed services along purely diagnostic lines.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0090.008
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.056
GPT teacher head0.396
Teacher spread0.340 · 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 designSystematic review
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

Citations9
Published2013
Admission routes1
Has abstractyes

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