{"id":"W2066581144","doi":"10.1002/sim.2546","title":"Bivariate models for co‐aggregation of dichotomous traits in twins","year":2006,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Reliability and Agreement in Measurement","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Bivariate analysis; Twin study; Correlation; Dizygotic twin; Trait; Statistics; Similarity (geometry); Econometrics; Dizygotic twins; Population; Genetic correlation; Monozygotic twin; Psychology; Heritability; Mathematics; Demography; Biology; Computer science; Medicine; Genetics; Genetic variation; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04060368,0.002156813,0.004255789,0.00386899,0.001468794,0.003637341,0.00601203,0.003333219,0.009657776],"category_scores_gemma":[0.07732524,0.001693295,0.003685676,0.004613254,0.003486443,0.003299774,0.004948427,0.004606626,0.002076764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002074696,"about_ca_system_score_gemma":0.002132916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02010086,"about_ca_topic_score_gemma":0.009987945,"domain_scores_codex":[0.9754341,0.01819992,0.0009669476,0.002424513,0.001609945,0.001364668],"domain_scores_gemma":[0.9188989,0.06363723,0.006030258,0.006564728,0.003495768,0.001373073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007396013,0.0003271084,0.0475716,0.00029932,0.001616608,0.001262156,0.002362719,0.278102,0.0005302093,0.6239213,0.004892541,0.03837479],"study_design_scores_gemma":[0.0001067144,0.0001748415,0.005681977,0.0001219687,0.0002835857,0.0002180574,0.0002218231,0.8257619,0.0001315923,0.164177,0.003024891,0.00009554024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1229032,0.001790849,0.8646479,0.00203755,0.0003907895,0.000621673,0.002345528,0.0004880384,0.004774533],"genre_scores_gemma":[0.7874436,0.003169089,0.1792951,0.0004467562,0.0005663427,0.003504114,0.003536264,0.0002093948,0.02182928],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04060368,"threshold_uncertainty_score":0.2147354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1356165566264823,"score_gpt":0.4075748772475037,"score_spread":0.2719583206210214,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}