Normal-range verbal-declarative memory in schizophrenia.
Bibliographic record
Abstract
OBJECTIVE: Cognitive impairment is prevalent and related to functional outcome in schizophrenia, but a significant minority of the patient population overlaps with healthy controls on many performance measures, including declarative-verbal-memory tasks. In this study, we assessed the validity, clinical, and functional implications of normal-range (NR), verbal-declarative memory in schizophrenia. METHOD: Performance normality was defined using normative data for 8 basic California Verbal Learning Test (CVLT-II; Delis, Kramer, Kaplan, & Ober, 2000) recall and recognition trials. Schizophrenia patients (n = 155) and healthy control participants (n = 74) were assessed for performance normality, defined as scores within 1 SD of the normative mean on all 8 trials, and assigned to normal- and below-NR memory groups. RESULTS: NR schizophrenia patients (n = 26) and control participants (n = 51) did not differ in general verbal ability, on a reading-based estimate of premorbid ability, across all 8 CVLT-II-score comparisons or in terms of intrusion and false-positive errors and auditory working memory. NR memory patients did not differ from memory-impaired patients (n = 129) in symptom severity, and both patient groups were significantly and similarly disabled in terms of functional status in the community. CONCLUSION: These results confirm a subpopulation of schizophrenia patients with normal, verbal-declarative-memory performance and no evidence of decline from higher premorbid ability levels. However, NR patients did not experience less severe psychopathology, nor did they show advantage in community adjustment relative to impaired patients. (PsycINFO Database Record
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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) | 0.001 | 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".