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Record W2165954253 · doi:10.1177/070674370705200707

Impairment of Autonoetic Awareness for Emotional Events in Schizophrenia

2007· article· en· W2165954253 on OpenAlexvenueno aff
Aurore Neumann, Pierre Philippot, Jean‐Marie Danion

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2007
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsEmotional valencePsychologyValence (chemistry)Schizophrenia (object-oriented programming)PsychosisCognitive psychologyAudiologyDevelopmental psychologyPsychiatryCognitionMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the subjective states of awareness accompanying recognition of emotional events in patients with schizophrenia. METHOD: During the learning phase, a set of neutral pictures associated with emotional sentences was presented to 24 patients with schizophrenia and 24 healthy control subjects. During the test phase, participants had to recognize target pictures and valence and to report their subjective state of awareness (Remember, Know, or Guess) associated with recognition of pictures and valence. RESULTS: Patients with schizophrenia exhibited poor recognition of pictures and emotional valence. The frequency of Remember responses associated with recognition of pictures and of valence was lower in patients than in control subjects. CONCLUSIONS: Autonoetic awareness for emotional events is reduced in schizophrenia, with patients presenting difficulties in consciously recollecting the specific details that make events emotional.

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)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.022
GPT teacher head0.311
Teacher spread0.289 · 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

Citations25
Published2007
Admission routes1
Has abstractyes

Explore more

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