F52. WHO CO-PARENT CHILDREN WITH MOTHERS AND FATHERS WITH SCHIZOPHRENIA OR BIPOLAR DISORDER? CHARACTERIZING INDIVIDUALS WHO HAVE CHILDREN TOGETHER WITH INDIVIDUALS WITH SCHIZOPHRENIA OR BIPOLAR DISORDER
Bibliographic record
Abstract
Prior studies have established that partners are similar to each other in many aspects. They correlate positively and strongly on age, social attitudes, and religiosity; correlate moderately on general intelligence, education, and physical attractiveness; and correlate weakly on height, weight, and personality traits. It remains unknown if and how this affects partners of individuals with schizophrenia or bipolar disorder. This aspect is clinically relevant when we want to characterize the risk factors for children growing up in families where one parent is living with schizophrenia or bipolar disorder. Therefore, the objective of this study is to investigate the diagnoses of a mental illness, cognitive ability, social functioning and polygenic risk in individuals who have children together with individuals with schizophrenia or bipolar disorder compared to controls. The Danish High Risk and Resilience Study - VIA7 is a nationwide cohort study conducted in Denmark between January 1, 2013 and January 31, 2016. The VIA7 cohort consists of 522 children aged 7 years with 0, 1 or 2 parents diagnosed with schizophrenia or bipolar disorder and both of their biological parents. Subjects were identified through the Danish Civil registration System and the Danish Psychiatric Central Research register. This study will focus on the biological co-parents (N = 443) without schizophrenia or bipolar disorder in the Danish registries. All participants were interviewed with SCAN and social functioning was measured using PSP. Further, we assessed intelligence (RIST), verbal working memory (Letter-Number Sequencing - WAIS-IV), and processing speed (Coding - WAIS-IV). Data analysis is on-going and data will be presented at the conference. Data analysis is on-going and data will be presented at the conference.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".