Clinical correlates of regional gray matter volumes in schizophrenia
Bibliographic record
Abstract
Objectives: The objective of this study is to investigate the correlation between the regional gray matter volumes and length of Para Cingulate Sulcus (PCS) with the clinical profile of patients with schizophrenia. Materials and Methods: In this hospital-based, cross-sectional study, thirty consecutive in-patients diagnosed with schizophrenia and equal number of healthy volunteers matched for age- and sex- were recruited as controls. Detailed clinical assessment and magnetic resonance imaging (MRI) of the brain were carried out within 2 days for controls and within 2 weeks of hospitalization for patients. The Positive and Negative Syndrome Scale and Montreal Cognitive Assessment were applied to schizophrenia patients to assess symptoms and cognitive function, respectively. Results: Schizophrenia patients had significant volume deficit in bilateral amygdalae, bilateral superior temporal gyri, anterior cingulate cortex and bilateral hippocampi, along with a highly significant reduction in the length of right PCS. Schizophrenia patients with the duration of untreated psychosis (DUP) of 6-12 months showed a significantly greater volume of the right superior temporal gyrus (STG). First-episode schizophrenia patients had a significant reduction in the length of the left PCS. The volume of bilateral superior temporal gyri in schizophrenia patients showed a significant direct correlation with positive symptoms and an inverse correlation with negative symptoms. Conclusion: Schizophrenia patients have significant volume deficit in some brain regions. DUP of 6-12 months is associated with significantly greater volume of the right STG. First-episode schizophrenia patients have a significant reduction in the length of the left PCS. In schizophrenia patients, the volume of bilateral superior temporal gyri showed a significant direct correlation with the positive symptoms and an inverse correlation with the negative symptoms.
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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 | 0.001 |
| 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) | 0.002 | 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".