Premonitory Urge in Patients with Tics and Functional Tic‐like Behaviors
Bibliographic record
Abstract
BACKGROUND: Premonitory urges (PU) are well described in primary tics, but their frequency and intensity in functional tic-like behaviors (FTLB) are unclear. OBJECTIVE: To study the experience of PU in patients with FTLB. METHODS: We compared the results of the premonitory urge for tics scale (PUTS) in adults with tics and FTLB in the University of Calgary Adult Tic Registry. RESULTS: We included 83 patients with tics and 40 with FTLB. When comparing patients with tics, FTLB with tics and FTLB only, we did not detect significant differences either in the total PUTS score (P = 0.39), or in any of the individual PUTS item sub-scores (P values ranging between 0.11 and 0.99). CONCLUSIONS: Patients with FTLB report PU at similar frequency and intensity to patients with tics. This finding confirms that PU are not a useful feature to discriminate FTLB from tics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".