{"id":"W2396009434","doi":"10.1002/gepi.2001.21.s1.s61","title":"Clustering of Pedigrees Using Marker Allele Frequencies: Impact on Linkage Analysis","year":2001,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; University of Toronto; Hospital for Sick Children; Toronto Western Hospital","funders":"Canadian Institutes of Health Research","keywords":"Pedigree chart; Genetics; Ethnic group; Allele; Locus (genetics); Microsatellite; Linkage (software); Genetic linkage; Biology; Cluster (spacecraft); Population; Evolutionary biology; Gene; Demography; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001573935,0.0003146963,0.0009280703,0.0002465805,0.0001039493,0.000004220953,0.0003344109,0.0004819193,0.0002600622],"category_scores_gemma":[0.001537433,0.0002658695,0.000603413,0.0004071548,0.0001990889,0.000002600207,0.0001585522,0.0001614197,0.00001487272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005604153,"about_ca_system_score_gemma":0.00009671362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006183081,"about_ca_topic_score_gemma":0.0002588663,"domain_scores_codex":[0.9966792,0.0009049673,0.0009648752,0.0006457714,0.0001030211,0.0007021496],"domain_scores_gemma":[0.9979467,0.0004392342,0.0005411197,0.0007682216,0.0001395129,0.0001652285],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007811179,0.00004920152,0.7728735,0.000008780316,0.0008468376,0.000004001709,0.00003080524,0.2099431,0.0135656,0.00001532487,0.0007593246,0.001825392],"study_design_scores_gemma":[0.0003804073,0.0006461779,0.9363226,0.000008856974,0.000351456,0.00004836853,0.00007040266,0.05947068,0.0002462398,0.0005645186,0.001582077,0.0003082634],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.861308,0.001593413,0.1356704,0.0001964985,0.0001252866,0.000154566,0.00003565163,0.00001218971,0.0009040077],"genre_scores_gemma":[0.9476146,0.001331056,0.04949281,0.0007027655,0.0003145928,0.00001661288,0.0001584853,0.00002836002,0.0003407302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1634491,"threshold_uncertainty_score":0.9999794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04350219174577,"score_gpt":0.3435748874328,"score_spread":0.30007269568703,"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."}}