Bibliographic record
Abstract
Compulsions are repetitive behaviors (e.g. washing, checking) and or mental acts (e.g. counting, reviewing) that an individual performs in response to rigid rules or as a way to reduce anxiety caused by obsessive thoughts. The most common types of compulsions include washing/cleaning, checking/rechecking, ordering/arranging, and counting. Some of the less common compulsions include gambling, shopping, hoarding, trichotillomania, or sexual behaviors. Although many healthy, normal individuals may engage in compulsive behaviors, what distinguishes normal and abnormal compulsions relates to the frequency, intensity, and discomfort of the behaviors. Compulsions are often time-consuming (e.g. more than one hour per day) and cause significant distress or impairment to an individual's daily functioning. Generally speaking, there are three types of treatment for compulsions: psychotherapy, pharmacotherapy, and brain modulation. Exposure and response prevention (ERP) is one of the most effective types of treatment for compulsive behaviors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 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".