The Correlation between the Indonesian Version of Montreal Cognitive Assessment and Homocysteine Levels in Bataknese Male with Schizophrenia in Prof. DR. M. Ildrem Psychiatric Hospital Medan
Bibliographic record
Abstract
BACKGROUND: The pathogenesis of schizophrenia and its mechanism is not convinced. Several studies indicate that schizophrenia pathogenesis can be related to changes at the cellular level. The studies show homocysteine in people with schizophrenia was significantly increased, abnormal homocysteine metabolism can lead to DNA methylation. AIM: This study aimed to establish the correlation between the Indonesian Montreal Cognitive Assessment Version (MoCA-Ina) scores and homocysteine levels in males with Bataknese schizophrenia. METHODS: This study is a numerical correlative analytic study with an approach to cross-sectional study; by evaluating the correlation between the MoCA-Ina scores and the level of homocysteine in males with Bataknese schizophrenia. RESULTS: The median of the MoCA-Ina score in the study subjects was 22, with a minimum score of 18 and a maximum score of 26. There was a significant correlation between the MoCA-Ina scores and Homocysteine levels (p = 0.001). CONCLUSION: The interpretation obtained from this study is that the higher Homocysteine level, the lower the MoCA-Ina scores in Bataknese men with schizophrenia is.
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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".