{"id":"W1570450173","doi":"","title":"Use of MACE Results as Input for Genomic Models","year":2011,"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":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mace; SNP; Computer science; Statistics; Biology; Genotype; Mathematics; Genetics; Medicine; Single-nucleotide polymorphism; Gene; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001046503,0.0003979117,0.0003224714,0.0001484693,0.0001011827,0.00005620055,0.0008687616,0.0003079252,0.004183714],"category_scores_gemma":[0.0006020158,0.0004197987,0.000254529,0.0000878882,0.0001136493,0.000009548937,0.000352378,0.0001600944,0.0005427718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006809551,"about_ca_system_score_gemma":0.0001866714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004975978,"about_ca_topic_score_gemma":0.00004715067,"domain_scores_codex":[0.996841,0.0002091824,0.001025722,0.0008799122,0.0006557452,0.0003885087],"domain_scores_gemma":[0.9965707,0.0001383528,0.0005975488,0.000722822,0.001815965,0.0001545882],"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":[0.02523045,0.00258088,0.000691979,0.0003838445,0.002471609,0.000005885299,0.005027595,0.09807306,0.07485685,0.05490009,0.7192536,0.01652417],"study_design_scores_gemma":[0.004495055,0.001235501,0.003808771,0.0001437072,0.0002237341,0.0000532511,0.0004080049,0.005159929,0.02747614,0.006815865,0.9494333,0.000746732],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7598115,0.00111332,0.104263,0.02299663,0.003082508,0.005271344,0.001824068,0.0001612502,0.1014763],"genre_scores_gemma":[0.867375,0.00008668287,0.1164726,0.004574935,0.0005387448,0.0004074782,0.001404046,0.0001047583,0.009035727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2301797,"threshold_uncertainty_score":0.9998254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1017321507210352,"score_gpt":0.2972714863572102,"score_spread":0.195539335636175,"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."}}