{"id":"W2150505604","doi":"","title":"De-regressing MACE versus domestic EBV for genomics","year":2015,"lang":"en","type":"article","venue":"Bulletin - International Bull Evaluation Service/Interbull bulletin","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Dairy Commission","funders":"","keywords":"Mace; Trait; Biology; Regression; Animal science; Statistics; Mathematics; Internal medicine; Medicine; Computer science","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00158748,0.0004151309,0.0002782343,0.0001162216,0.0001547848,0.0001851135,0.0008765518,0.0003090327,0.002114979],"category_scores_gemma":[0.001187058,0.000447498,0.0001978127,0.00009092648,0.0001002312,0.000005363119,0.0003035143,0.0001973579,0.000830412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003278673,"about_ca_system_score_gemma":0.0004860621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009396364,"about_ca_topic_score_gemma":0.00003155598,"domain_scores_codex":[0.9970744,0.0002331587,0.000630947,0.0008055247,0.0007303746,0.0005255624],"domain_scores_gemma":[0.996985,0.0001762617,0.0003521678,0.0005446667,0.001629351,0.0003126047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01120909,0.0007315399,0.0004141218,0.0001539369,0.001027856,0.000007182982,0.001329569,0.08838776,0.0161187,0.007566546,0.8540547,0.01899899],"study_design_scores_gemma":[0.006350574,0.0007610402,0.0006014411,0.00007202062,0.0001699693,0.0000724638,0.0006483705,0.004376892,0.003072305,0.001464436,0.9818772,0.0005332701],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5622182,0.004496274,0.2418806,0.1013171,0.01064784,0.00462705,0.0005685119,0.000293195,0.07395121],"genre_scores_gemma":[0.7905164,0.00005888228,0.1822471,0.009115,0.003345221,0.000848242,0.002061957,0.0002017882,0.01160534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2282982,"threshold_uncertainty_score":0.9999475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0605493218713211,"score_gpt":0.3396672071486851,"score_spread":0.279117885277364,"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."}}