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Record W2022582825 · doi:10.1159/000287762

Epidemiology of Psychosomatic Disorders in Schizophrenic Patients: Methodological Issues

2010· article· en· W2022582825 on OpenAlexaff
R.A. Ramsay, F. Engelsmann

Bibliographic record

VenuePsychotherapy and Psychosomatics · 2010
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Epidemiology
Canadian institutionsMcGill University
Fundersnot available
KeywordsEpidemiologyPsychiatryRepresentativeness heuristicInter-rater reliabilityMedical diagnosisSchizophrenia (object-oriented programming)PopulationPsychologyPsychiatric diagnosisClinical psychologyPsychiatric epidemiologyMedicineMental healthDevelopmental psychologyRating scale

Abstract

fetched live from OpenAlex

The value of an epidemiological study investigating the prevalence of certain somatoform diseases in schizophrenic patients can be strengthened by attention to the following methodological principles: (1) sufficient size of sample; (2) representativeness of sample, controlling if possible such variables as age range, inpatient or outpatient status, ward population or milieu and cultural aspects; (3) study of control groups in same milieu with other psychiatric diagnoses; (4) clear specification of diagnostic criteria employed; (5) establishment of interrater reliability concerning psychiatric diagnosis, patient historical data or medical record information.

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)0.396
metaresearch head score (Gemma)0.559
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.604
Threshold uncertainty score0.745

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3960.559
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.006
Science and technology studies0.0020.008
Scholarly communication0.0030.004
Open science0.0040.005
Research integrity0.0030.002
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 head0.178
GPT teacher head0.497
Teacher spread0.319 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations2
Published2010
Admission routes1
Has abstractyes

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