{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02168193,0.0008772016,0.001076448,0.002682526,0.0009793302,0.001268136,0.0009392196,0.0005541447,0.001186655],"category_scores_gemma":[0.08860566,0.000369001,0.0008943647,0.003302527,0.0007182977,0.001316317,0.001316535,0.0006271289,0.000239495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005427571,"about_ca_system_score_gemma":0.000788677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00851136,"about_ca_topic_score_gemma":0.00879189,"domain_scores_codex":[0.9551125,0.03911777,0.0008249306,0.002212339,0.002293689,0.0004387562],"domain_scores_gemma":[0.8789026,0.1053806,0.005327829,0.007053756,0.002463741,0.000871613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001629261,0.000206822,0.8095577,0.0001982112,0.003113,0.001096011,0.001974943,0.04408288,0.005737749,0.002750501,0.001374959,0.1282781],"study_design_scores_gemma":[0.0002137779,0.0007735826,0.6829413,0.0001303905,0.001503706,0.001631089,0.001211508,0.2933532,0.004098315,0.01045756,0.003508776,0.0001767946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9316137,0.0005435331,0.06496045,0.0003421963,0.00003107302,0.00009636083,0.0002560839,0.0002567956,0.001899718],"genre_scores_gemma":[0.9732649,0.0001388805,0.02595561,0.00003459074,0.00001411851,0.0000459764,0.0002354298,0.00006011696,0.0002502416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02168193,"threshold_uncertainty_score":0.1146664,"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."}}