Deep brain stimulation for movement disorders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE OF REVIEW: The purpose of this review was to review the recent and future developments of deep brain stimulation (DBS) for movement disorders. RECENT FINDINGS: In the last 2 years, we have gained a better understanding of established indications, particularly with respect to the debate on whether subthalamus or globus pallidus pars interna should be the target of choice for Parkinson's disease. In addition, the role of DBS for dystonia has been further defined in terms of patients' selection and outcome of surgery. Other established (e.g. essential tremor) and novel indications (e.g. Tourette syndrome) have been addressed. Along with the evolving knowledge of the clinical aspects of DBS, technological advances are also shaping the present and the future of DBS. New implantable pulse generators (e.g. allowing storage of electrophysiological data and eventual adaptive stimulation) as well as new electrode configurations are now available. Furthermore, high-resolution structural imaging, including high-field MRI and diffusion tensor tractography, will facilitate both the planning of DBS procedures, and the optimization of postoperative outcomes by aiding stimulation programming. SUMMARY: The recent successes of DBS along the clinical and technological directions are changing the current practice of neuromodulation and, more importantly, will also drive future developments of this fascinating treatment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it