Milestones in Tremor Research: 10 Years Later
Bibliographic record
Abstract
Major progress has occurred during the last decade in the field of tremor. From the clinical standpoint, a new classification has completely revised the nosology of tremor syndromes and has re-conceptualized essential tremor as a syndrome rather than a single disease entity, fueling an ongoing enlightened debate. Significant advances have been obtained in terms of instrumental measurement of tremor, remarking on the possibility of developing novel treatment strategies based on tremor characteristics, namely tremor-phase. Moreover, a better understanding of the pathophysiological mechanisms has further led to the suggestion of refining the classification of tremor syndromes according to their driving underpinnings. Finally, surgical options such as deep brain stimulation and focused ultrasound thalamotomy are now part of the therapeutic portfolio for tremor, but several oral drugs, including long-chain alcohols, T-channel blockers, allosteric modulators of potassium channels, and of GABA-A receptors, are currently being tested and hold promise. This review will discuss the key milestones in tremor research of the last 10 years, with a focus on the most common tremor syndromes, namely essential tremor, dystonic tremor, and Parkinsonian tremor.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".