No, It Is Not Possible to Be Schizophrenic Yet Neuropsychologically Normal.
Bibliographic record
Abstract
Cognitive impairment is well documented in schizophrenia, though some reports have been interpreted to suggest that it is possible to have schizophrenia without neuropsychological impairment. The authors tested this by comparing the neuropsychological profiles of closely matched patients with schizophrenia and healthy comparison participants. Sixty-four patients with schizophrenia and 64 healthy comparison cases, matched to within 3 Full-Scale IQ points, were tested using the Wechsler Adult Intelligence Scale (3rd ed.; D. Wechsler, 1997b) and the Wechsler Memory Scale (3rd ed.; D. Wechsler, 1997c). Neuropsychological profiles for these groups were markedly different, with the group of patients with schizophrenia exhibiting performance deficits in memory and speeded visual processing but superior verbal comprehension and perceptual organization relative to the group of healthy comparison participants matched on Full-Scale IQ. Thus, scoring in the normal range does not preclude neuropsychological abnormality in schizophrenia, confirming that neuropsychological impairment is a core feature of the illness.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".