[Retracted] Measuring Subthalamic Nucleus Volume of Parkinson’s Patients and Evaluating Its Relationship with Clinical Scales at Pre‐ and Postdeep Brain Stimulation Treatment: A Magnetic Resonance Imaging Study
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
This study investigated potential imaging biomarkers for predicting the efficacy of deep brain stimulation (DBS) of the subthalamic nucleus (STN) in patients with Parkinson's disease (PD). A total of 59 PD patients and 50 healthy control subjects underwent high-resolution 3-dimensional T1-weighted brain magnetic resonance imaging. Bilateral STN volumes were compared between the 2 groups, and a correlation analysis was performed to assess the relationship between bilateral STN volumes or intracranial volume (ICV) and pre- or postoperative clinical scale scores. The results showed that the left STN volume differed significantly between PD patients and controls. In patients, the left STN volume was negatively correlated with pre- and postoperative quality of life scores and positively correlated with Mini-mental State Examination (MMSE) and Montreal Cognitive Assessment scores; ICV was also positively correlated with the MMSE score. These findings indicate that changes in the left STN volume are a useful biomarker for evaluating the clinical outcome of PD patients following DBS.
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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 | 0.000 | 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".