{"id":"W2109641307","doi":"10.1093/bioinformatics/18.6.894","title":"DMLE+: Bayesian linkage disequilibrium gene mapping","year":2002,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institutes of Health; Canadian Institutes of Health Research; Killam Trusts; National Human Genome Research Institute; Fondation pour la Recherche Médicale","keywords":"Linkage disequilibrium; Bayesian probability; Linkage (software); Disequilibrium; Computational biology; Genetics; Computer science; Gene; Biology; Artificial intelligence; Haplotype; Allele; Medicine","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":[0.002973082,0.001231747,0.001375522,0.001769492,0.0007272994,0.001614375,0.002826086,0.0007661376,0.05656905],"category_scores_gemma":[0.008841963,0.001202265,0.001083697,0.001502681,0.0003584614,0.001105159,0.002067222,0.001665742,0.02065723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004226581,"about_ca_system_score_gemma":0.000918559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001608552,"about_ca_topic_score_gemma":0.002205848,"domain_scores_codex":[0.9986039,0.0006337389,0.00007728262,0.0002958009,0.0002967307,0.0000925634],"domain_scores_gemma":[0.9973313,0.001984965,0.0001656399,0.0002068066,0.0002039641,0.0001073189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001334435,0.0002422959,0.006379881,0.001743802,0.0008483466,0.000661602,0.0004149635,0.06388234,0.007992024,0.04236867,0.4870503,0.3870813],"study_design_scores_gemma":[0.002072152,0.0001265025,0.004207274,0.0002930784,0.0002778549,0.001103824,0.00007557847,0.5293057,0.0190562,0.1253482,0.3178923,0.000241362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005622306,0.0003476565,0.8424224,0.0004525053,0.0001328338,0.0002149271,0.03552305,0.1074727,0.007811547],"genre_scores_gemma":[0.0617707,0.0003585822,0.8727089,0.0005544783,0.00009483269,0.001996282,0.03740579,0.01623612,0.008874319],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05656905,"threshold_uncertainty_score":0.1892423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01966016657473886,"score_gpt":0.2320162652202325,"score_spread":0.2123560986454937,"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."}}