Etiology of obsessions and compulsions: A behavioral-genetic analysis.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
It is unknown whether various types of obsessive-compulsive (OC) symptoms have a common genetic or environmental etiology. For example, it is unknown whether hoarding is etiologically associated with prototypic OC symptoms, such as washing, checking, and obsessing. Also unknown is whether particular OC-related symptoms are etiologically linked to the general tendency to experience emotional distress (negative emotionality). To investigate these and other issues, a community sample of 307 pairs of monozygotic and dizygotic adult twins provided scores on 6 OC-related symptoms (obsessing, neutralizing, checking, washing, ordering, and hoarding) and 2 markers of negative emotionality (trait anxiety and affective lability). Genetic factors accounted for 40%-56% of variance in the 8 phenotypic scores (M = 49% of variance for OC-related symptoms). Remaining variance was due to nonshared (person-specific) environment. More detailed analyses revealed a complex etiologic architecture, where OC-related symptoms arise from a mix of common and symptom-specific genetic and environmental factors. A general genetic factor was identified, which influenced all symptoms and negative emotionality. An environmental factor was identified that influenced all symptoms but did not influence negative emotionality. Each of the 6 types of symptoms was also shaped by its own set of symptom-specific genetic and environmental factors. The importance of genetic factors did not vary as a function of age or sex, and the architecture of general and specific etiologic factors was replicated for participants having relatively more severe OC symptoms. Gene-environment interactions were identified. Implications for an etiology-based classification system are discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it