{"id":"W2122705486","doi":"10.1002/gepi.20220","title":"Optimal selection of markers for validation or replication from genome‐wide association studies","year":2007,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Genome Canada","keywords":"Genotyping; Single-nucleotide polymorphism; Candidate gene; Computational biology; Biology; SNP; Selection (genetic algorithm); Genetics; Genome-wide association study; Genome; Gene; Genotype; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005421925,0.0002052186,0.0005704078,0.00009710025,0.0001277997,0.000003149567,0.0001833588,0.0005164815,0.00003448089],"category_scores_gemma":[0.03396983,0.0001887877,0.0001797782,0.0001584735,0.00008433194,0.000004388388,0.00007328488,0.00009668779,0.000007006234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001682287,"about_ca_system_score_gemma":0.00009956327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007923705,"about_ca_topic_score_gemma":0.0001763202,"domain_scores_codex":[0.9969832,0.0005451004,0.001153176,0.0006963834,0.00009480014,0.0005273734],"domain_scores_gemma":[0.9933679,0.004484553,0.001094772,0.0004539198,0.0005163379,0.00008255745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006519584,0.00006546586,0.9013403,0.00003310034,0.0006735556,2.635801e-7,0.00009589593,0.006419605,0.06684833,0.00005239582,0.01622045,0.007598666],"study_design_scores_gemma":[0.0008746328,0.0009555078,0.947333,0.00001070471,0.0001668679,0.000004626501,0.0002821745,0.0008904091,0.02265129,0.002328089,0.02422352,0.0002791498],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7436174,0.00118275,0.2532981,0.001027492,0.0002776074,0.0004609428,0.00005100522,0.00001658705,0.00006817707],"genre_scores_gemma":[0.7391574,0.00153057,0.2549278,0.001468001,0.0006883035,0.0001598916,0.0008957071,0.00003633697,0.001135966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04599272,"threshold_uncertainty_score":0.9741675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04717341177972235,"score_gpt":0.3538177349263996,"score_spread":0.3066443231466772,"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."}}