Lessons from a multicenter, international, large sample size analysis of patients with obsessive–compulsive disorders: an overview of the ICOCS Snapshot studies
Bibliographic record
Abstract
Obsessive-compulsive disorder (OCD) is a prevalent and highly disabling condition, characterized by a range of phenotypic expressions, potentially associated with geo-cultural differences. This article aims to provide an overview of the published studies by the International College of Obsessive-Compulsive Spectrum Disorders, in relation to the Snapshot database which has, over the past 10 years, gathered clinical naturalistic data from over 500 patients with OCD attending various research centers/clinics worldwide. This collaborative effort has provided a multi-cultural worldwide perspective of different socio-demographic and clinical features of patients with OCD. Data on age, gender, smoking habits, age at onset, duration of illness, comorbidity, suicidal behaviors, and pharmacological treatment strategies are presented here, showing peculiar differences across countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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 teacher head, 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".