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Record W3164656646 · doi:10.3892/etm.2021.10237

Behavioral outputs of negative symptom domains of schizophrenia

2021· article· en· W3164656646 on OpenAlexaboutno aff
Octavia Căpățînă, Mihaela Fadgyas Stănculete, I. Micluția

Bibliographic record

VenueExperimental and Therapeutic Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)ApathyPositive and Negative Syndrome ScaleClinical psychologyPsychologyRating scaleAnalysis of varianceAnalysis of covarianceBody mass indexDepression (economics)PsychiatryMedicinePsychosisInternal medicineDevelopmental psychologyStatisticsCognition

Abstract

fetched live from OpenAlex

The present study aimed to validate the hypothesis that negative symptoms of schizophrenia encompass two domains, namely avolition-apathy (AA) and diminished expression (DE), and to investigate the relationship of these domains with behavioral outputs which imply hedonic activities: Cigarette use and weight gain. A total of 106 consecutive schizophrenia outpatients with primary negative symptoms were evaluated using the Positive and Negative Syndrome Scale (PANSS), the Negative Symptoms Assessment Scale (NSA-16), the Calgary Depression Scale for Schizophrenia (CDSS), and the Simpson-Angus Scale (SAS). A semi-structured interview was used to assess demographic features, the number of cigarettes smoked per day, and body mass index. Data were analyzed using descriptive statistics, principal component analysis, analysis of variance, and covariance. A two-factor solution was revealed for the negative symptoms of schizophrenia represented by AA and DE. Analyses of variance and covariance suggested that higher AA scores were associated with normal weight and non-smoking status. No significant differences were revealed regarding DE scores in relationship with the same behavioral hedonic outputs. The present results indicated the AA and DE domains exhibit meaningful differences concerning the outcome, which may imply the need for different approaches regarding rating and treatment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.351
Teacher spread0.312 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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