{"id":"W7029071842","doi":"","title":"Imputing Genotypes Using Regularized Generalized Linear Regression Models","year":2012,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Imputation (statistics); Missing data; Multicollinearity; International HapMap Project; Context (archaeology); Linear regression; Linear model; Data set; Regression","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01387946,0.001636859,0.00233169,0.001637112,0.0005402801,0.001615104,0.00406537,0.00194245,0.003145779],"category_scores_gemma":[0.02705768,0.001296637,0.003650398,0.002359481,0.000854097,0.001579517,0.001620115,0.003097133,0.001695437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008836216,"about_ca_system_score_gemma":0.00206288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009755068,"about_ca_topic_score_gemma":0.008882107,"domain_scores_codex":[0.9911238,0.006619301,0.0002602395,0.001191538,0.000522223,0.0002828259],"domain_scores_gemma":[0.9873487,0.009031507,0.0008161913,0.00158893,0.001040868,0.0001739712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003337931,0.0001111144,0.003359023,0.0001271129,0.0005675038,0.0002710046,0.0001452383,0.9039647,0.000790161,0.01416995,0.003667222,0.07249321],"study_design_scores_gemma":[0.00002493569,0.00002730349,0.0002181905,0.000007757509,0.0000241169,0.00002987353,0.000006291137,0.9909842,0.0001842639,0.007851449,0.0006247326,0.00001678632],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008280491,0.0001241207,0.9898545,0.0001799595,0.00003124074,0.00006766062,0.0003724023,0.0008795038,0.0002101501],"genre_scores_gemma":[0.2202245,0.0003613343,0.7709851,0.0003668747,0.0001420095,0.0005418285,0.002945279,0.0005517676,0.003881219],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01387946,"threshold_uncertainty_score":0.07340246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02158744937469391,"score_gpt":0.247192027460455,"score_spread":0.2256045780857611,"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."}}