Bibliographic record
Abstract
PURPOSE OF REVIEW: This paper reviews the recent literature concerning Tourette syndrome and related disorders. RECENT FINDINGS: Tourette syndrome is a common disorder in children and adolescents, with an established association with attention deficit hyperactivity disorder, obsessive compulsive disorder, and a number of other psychiatric disorders. Both autoimmune and genetic mechanisms are implicated in the pathophysiology of the syndrome, while neuroimaging studies have identified abnormalities in the composition of the basal ganglia and frontal lobe white matter, as well as alterations in dopaminergic activity. When necessary, treatment of tics can be successful with neuroleptics and alpha-2-adrenergic agonists. The use of stimulants in children with Tourette syndrome and comorbid attention deficit hyperactivity disorder does not appear to worsen tics. SUMMARY: As a result of the recent literature, clinicians can feel comfortable treating children with co-morbid attention deficit hyperactivity disorder and Tourette syndrome with stimulant medications. It has also been established that transient tics are very common in children, and for the most part, non-disabling. In those children with persistent tics, behavioural disorders are associated which may impair success in school and psychosocial functioning. Clinicians have a number of therapeutic options, with recent double-blinded randomized trials of clonidine, risperidone, and desipramine showing benefit. Scientists continue to search for the cause of Tourette 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.024 |
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".