“Unvoluntary” Movement Disorders: Distinguishing between Tics, Akathisia, Restless Legs, and Stereotypies
Bibliographic record
Abstract
Tics, stereotypies, akathisia, and restless legs fall at different places on the spectrum of discrete, unwanted and potentially disabling motor routines. Unlike tremor, chorea, myoclonus, or dystonia, this subgroup of abnormal movements is characterized by the subject's variable ability to inhibit or release undesired motor patterns on demand. Though it may be sometimes clinically challenging, it is crucial to distinguish these "unvoluntary" motor behaviors because secondary causes and management approaches differ substantially. To this end, physicians must consider the degree of repetitiveness of the movements, the existence of volitional control, and the association with sensory symptoms, or cognitive-ideational antecedent. This review aims to summarize the current existing knowledge on phenomenology, diagnosis, and treatment of tics, stereotypies, akathisia, and restless leg syndrome.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".