Neurocognitive normality in schizophrenia revisited
Bibliographic record
Abstract
The validity and significance of normal range neurocognition in schizophrenia remain unclear and controversial. We assessed whether normal range patients and controls demonstrate evidence of decline relative to premorbid ability and differ in performance profiles across measures, including those external to the normality criterion. In addition, we compared below normal range healthy control participants with patients at the same ability level. Performance normality was defined as a MATRICS Consensus Cognitive Battery (MCCB) composite T score between 40 and 60. Patients (n = 17) and controls (n = 24) meeting the criterion were compared on MCCB domain scores and on independent measures of reading ability, probabilistic and social reasoning. Patients (n = 19) and controls (n = 20) scoring below 40 on the MCCB composite were compared on the same set of measures. Cognitively normal range patients and controls did not differ on estimated premorbid ability or decline and differed only on the Processing Speed domain of the MCCB. Performance did not differ across other domains or on social and probabilistic reasoning tasks. Cognitively below normal range patients and controls showed marked discrepancies between premorbid and current ability, but there were no group differences. In addition, below normal range groups did not differ on any MCCB domain score or in terms of external cognitive measures. Cognitively normal range schizophrenia patients may be largely indistinguishable from normal range controls, with the exception of processing speed performance. More typical schizophrenia patients below the normal range may be indistinguishable from low-performing controls even in terms of processing speed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".