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Record W2167692459 · doi:10.1080/08870446.2010.519769

Emotion recognition and emotional theory of mind in chronic fatigue syndrome

2011· article· en· W2167692459 on OpenAlexaff
Anna Oldershaw, David Hambrook, Katharine A. Rimes, Kate Tchanturia, Janet Treasure, Selwyn Richards, Ulrike Schmidt, Trudie Chalder

Bibliographic record

VenuePsychology and Health · 2011
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsSt. Thomas Hospital
FundersNational Institute for Health and Care Research
KeywordsPsychologyEmotion recognitionChronic fatigue syndromeTheory of mindInferenceFunction (biology)Social functionClinical psychologyCognitionPsychiatryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Difficulties with social function have been reported in chronic fatigue syndrome (CFS), but underpinning factors are unknown. Emotion recognition, theory of mind (inference of another's mental state) and 'emotional' theory of mind (eToM) (inference of another's emotional state) are important social abilities, facilitating understanding of others. This study examined emotion recognition and eToM in CFS patients and their relationship to self-reported social function. METHODS: CFS patients (n = 45) and healthy controls (HCs; n = 50) completed tasks assessing emotion recognition, basic or advanced eToM (for self and other) and a self-report measure of social function. RESULTS: CFS participants were poorer than HCs at recognising emotion states in the faces of others and at inferring their own emotions. Lower scores on these tasks were associated with poorer self-reported daily and social function. CFS patients demonstrated good eToM and performance on these tasks did not relate to the level of social function. CONCLUSIONS: CFS patients do not have poor eToM, nor does eToM appear to be associated with social functioning in CFS. However, this group of patients experience difficulties in emotion recognition and inferring emotions in themselves and this may impact upon social function.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.200
GPT teacher head0.402
Teacher spread0.202 · 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 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

Citations19
Published2011
Admission routes1
Has abstractyes

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