Decision‐making in Parkinson’s disease patients with and without pathological gambling
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Pathological gambling (PG) in Parkinson's disease (PD) is a frequent impulse control disorder associated mainly with dopamine replacement therapy. As impairments in decision-making were described independently in PG and PD, the objective of this study was to assess decision-making processes in PD patients with and without PG. METHODS: Seven PD patients with PG and 13 age, sex, education and disease severity matched PD patients without gambling behavior were enrolled in the study. All patients were assessed with a comprehensive neuropsychiatric and cognitive evaluation, including tasks used to assess decision-making abilities under ambiguous or risky situations, like the Iowa Gambling Task (IGT), the Game of Dice Task and the Investment Task. RESULTS: Compared to PD patients without gambling behavior, those with PG obtained poorer scores in the IGT and in a rating scale of social behavior, but not in other decision-making and cognitive tasks. CONCLUSIONS: Low performance in decision-making under ambiguity and abnormal social behavior distinguished PD patients with PG from those without this disorder. Dopamine replacement therapy may induce dysfunction of the ventromedial prefrontal cortex and amygdala-ventral striatum system, thus increasing the risk for developing PG.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".