Impaired recognition of happy facial expressions in bipolar disorder
Bibliographic record
Abstract
BACKGROUND: The ability to accurately judge facial expressions is important in social interactions. Individuals with bipolar disorder have been found to be impaired in emotion recognition; however, the specifics of the impairment are unclear. This study investigated whether facial emotion recognition difficulties in bipolar disorder reflect general cognitive, or emotion-specific, impairments. Impairment in the recognition of particular emotions and the role of processing speed in facial emotion recognition were also investigated. METHODS: Clinically stable bipolar patients (n = 17) and healthy controls (n = 50) judged five facial expressions in two presentation types, time-limited and self-paced. An age recognition condition was used as an experimental control. RESULTS: Bipolar patients' overall facial recognition ability was unimpaired. However, patients' specific ability to judge happy expressions under time constraints was impaired. CONCLUSIONS: Findings suggest a deficit in happy emotion recognition impacted by processing speed. Given the limited sample size, further investigation with a larger patient sample is warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".