Standard guidelines for publication of deep brain stimulation studies in Parkinson's disease (Guide4DBS‐PD)
Bibliographic record
Abstract
While the use of deep brain stimulation (DBS) for the treatment of neurological disorders has risen substantially over the last decade, it is often difficult to compare the results from different studies due to the lack of consistent reporting of key study parameters. We present guidelines to standardize the reporting of clinical studies of DBS for Parkinson's disease (PD). These guidelines provide a minimal set of required data elements to facilitate the interpretation and comparison of results across published clinical studies. The guidelines, summarized in the format of a checklist, may also have utility in the planning of clinical studies of DBS for PD as well as other neurological and psychiatric disorders.
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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 | 0.195 | 0.384 |
| Meta-epidemiology (narrow) | 0.003 | 0.007 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.031 | 0.022 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.013 | 0.008 |
| Research integrity | 0.019 | 0.015 |
| Insufficient payload (model declined to judge) | 0.027 | 0.038 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".