Cognitive processing of facial affect: Connectionist model of deviations in schizophrenia.
Bibliographic record
Abstract
Connectionist-model simulations of competing hypotheses of cognition in schizophrenia were constructed and tested. Emphasis was placed on judgment of affect, a prominent area of disturbance in this disorder with potential implications for social impairment. Participants with paranoid or nonparanoid schizophrenia and control participants provided judgments of affect as expressed in photographic faces. Schizophrenia groups were less accurate than control groups, and the paranoid group had greater latencies than did other groups. Model predictions simultaneously addressed judgment content and latencies for each trial. Results provide a connectionist extension of an account of deficits in schizophrenia that originated at the computational (stochastic modeling) level of analysis. This account postulates extra stages of item encoding but no reduction in formally defined processing capacity. It also provides for abnormalities in both judgment patterns and duration and is consistent with biological accounts of schizophrenia deficits. The substantive findings are supported by strategic innovations in the construction and testing of connectionist models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".