The impact of assortative mating, participation bias, and socioeconomic status on the polygenic risk of behavioral and psychiatric traits
Bibliographic record
Abstract
Abstract To investigate assortative mating (AM), participation bias, and socioeconomic status (SES) with respect to the genetics of behavioral and psychiatric traits, we analyzed gametic phase disequilibrium (GPD), within-spouses and within-siblings polygenic risk score (PRS) correlation, performing a SES conditional analysis. We observed genetic signatures of AM across multiple methods for traits related to substance use with SES conditioning increasing the within-spouses PRS correlation for Frequency of drinking alcohol (2.5% to 6%), Maximum habitual alcohol intake (1.33% to 4.43%), and Ever taken cannabis (1.5% to 5.3%). Comparing UK Biobank mental health questionnaire responders vs. non-responders, major depressive disorder PRS showed significant GPD in both groups when based on the Million Veteran Program (3.2% vs. 3%), but only in responders when based on the Psychiatric Genomics Consortium (3.8% vs. 0.2%). These results highlight the impact of AM, participation bias, and SES on the polygenic risk of behavioral and psychiatric traits.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".