{"id":"W2954126010","doi":"10.3168/jds.2019-16265","title":"Invited review: Advances and applications of random regression models: From quantitative genetics to genomics","year":2019,"lang":"en","type":"review","venue":"Journal of Dairy Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Biology; Selection (genetic algorithm); Regression; Genomics; Computational biology; Quantitative trait locus; Genomic selection; Phenotypic trait; Evolutionary biology; Genetics; Phenotype; Statistics; Genome; Single-nucleotide polymorphism; Computer science; Machine learning; Gene; Genotype; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005267211,0.0001963238,0.0008326666,0.000130153,0.00005855839,0.0000162009,0.0006961973,0.0001113975,0.000002071448],"category_scores_gemma":[0.0001416406,0.0001368789,0.0001661016,0.000307188,0.0002793301,0.00001386477,0.0001927609,0.0001557365,0.000001534311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001889932,"about_ca_system_score_gemma":0.0004066692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001425331,"about_ca_topic_score_gemma":0.000001090989,"domain_scores_codex":[0.9984393,0.00008823565,0.0007210577,0.0003196816,0.0002878693,0.0001438482],"domain_scores_gemma":[0.9980592,0.00008384954,0.001024255,0.0003833454,0.0003083079,0.0001410264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005677225,0.00004739422,0.000009503286,0.00513409,0.00007415562,3.086737e-7,0.0001083752,0.0006971188,0.001186123,0.0001013518,0.001188911,0.9913959],"study_design_scores_gemma":[0.000286584,0.0004431151,0.00002641783,0.008664204,0.0003447059,0.0000222105,0.00004219346,0.00001834836,0.0001718963,0.0007892134,0.9890002,0.0001909326],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003832965,0.9626483,0.03604479,0.00003795962,0.0001714565,0.0005619954,0.00009305399,9.871842e-7,0.00005819567],"genre_scores_gemma":[0.00003478064,0.9261395,0.07346357,0.000177204,0.000122234,0.00001083881,0.00001607763,0.00001237524,0.00002340717],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.991205,"threshold_uncertainty_score":0.5581759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04442058411816724,"score_gpt":0.3520863318337381,"score_spread":0.3076657477155708,"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."}}