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Record W7054556232

Alexithymie und emotionale Intelligenz bei Schizophrenie

2007· dissertation· de· W7054556232 on OpenAlexaboutno aff

Bibliographic record

VenueURN:NBN Resolver for Germany & Switzerland (German National Library) · 2007
Typedissertation
Languagede
FieldEngineering
TopicMagneto-Optical Properties and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101DiafiltrationHyporeflexiaDysgeusiaLiquationFusible alloy
DOInot available

Abstract

fetched live from OpenAlex

In vorliegender Arbeit wurde Alexithymie und emotionale Intelligenz schizophrener Patienten mit der von Normalprobanden und depressiven Patienten verglichen. Zudem wurde exploriert, ob diese bei schizophrenen Patienten mit Personen- und Erkrankungsmerkmalen zusammenhängen. 31 schizophrenen Patienten, 50 depressiven Patienten und 100 Studenten wurden die Toronto-Alexithymie-Skala, die Emotionale Intelligenz-Skala und weitere Fragebögen vorgegeben. Die schizophrenen Patienten erreichten höhere Alexithymiewerte und zeigten eine niedrigere emotionale Intelligenz. Bei Kontrolle der Zustandsdepressivität wurde allerdings nur noch ein Gruppenunterschied im extern orientierten Denken bzw. eine Tendenz zu einer geringeren situationalen emotionalen Intelligenz ermittelt. Die Persönlichkeit schizophren Erkrankter zeichnete sich gegenüber den Gesunden v.a. durch eine erhöhte Introversion aus. Alexithymie und emotionale Intelligenz korrelierten erwartungsgemäß negativ miteinander.

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)0.002
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.303
Teacher spread0.285 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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