The Core Deficit of Classical Schizophrenia: Implications for Predicting the Functional Outcome of Psychotic Illness and Developing Effective Treatments
Bibliographic record
Abstract
Many people suffering from psychotic illnesses experience persisting impairment of occupational and social function. Evidence assembled since the classical description of schizophrenia over a century ago indicates that both disorganization and impoverishment of mental activity are associated with persisting impairment. Longitudinal studies of young people at risk of schizophrenia reveal that both mental impoverishment and disorganization predict poor long-term outcome. These clinical features are related to cognitive impairments. Evidence from brain imaging indicates overlap in the brain abnormalities implicated in these phenomena, including impaired function of long-range connections between sensory cortex and the salience network, a network engaged in recruiting cerebral systems for processing of information salient to current circumstances. The evidence suggests that the common features underlying these two groups of symptoms might reflect a core pathological process distinguishing nonaffective from affective psychosis. This pathological process might therefore justifiably be designated the "core deficit" of classical schizophrenia. To develop more effective treatments to prevent persisting disability, we require the ability to identify individuals at risk at an early stage. Recent studies provide pointers toward effective strategies for identifying cases at risk of poor outcome. Accumulating evidence confirms that appreciable potential for neuroplastic change in the brain persists into adult life. Furthermore, brain function can be enhanced by targeted neuromodulation treatments. We now have promising tools not only for investigating the psychological and neural mechanisms that underlie persisting functional impairment but also for identifying individuals at risk and for harnessing brain plasticity to improve treatment.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".