Could cognitive impairment manifest in Behçet's disease even in the absence of neurological symptoms?
Bibliographic record
Abstract
Purpose: Behçet's disease (BD) is a chronic, multisystem inflammatory disorder that causes mortality and morbidity. Despite data indicating cognitive impairment in patients without neurological involvement, there is currently no consensus on how to screen patients. The Montreal Cognitive Assessment (MOCA) is a practical, easy-to-use screening scale that can detect mild cognitive impairment. We aimed to detect cognitive dysfunction with MOCA in BD without neurological findings. Materials and methods: This prospective study included patients diagnosed with BD without neurological findings, and healthy individuals matched for age, gender, and education. Behçet's Disease Current Activity Form (BDCAF) was applied to determine disease activity, and MOCA was applied to all participants. Results: The total score of the MOCA scale was significantly lower in Behçet's patients than in the control group (p0.05), scores in other subtests were significantly lower in patients (p
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".