{"id":"W3013519488","doi":"10.1002/tpg2.20002","title":"Genomic selection for lentil breeding: Empirical evidence","year":2020,"lang":"en","type":"article","venue":"The Plant Genome","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Saskatchewan Pulse Growers; Genome Prairie; Western Grains Research Foundation; University of Saskatchewan; Genome Canada","keywords":"Biology; Trait; Quantitative trait locus; Heritability; Population; Selection (genetic algorithm); Best linear unbiased prediction; Genomic selection; Plant breeding; Predictive modelling; Genetics; Genotype; Statistics; Agronomy; Machine learning; Single-nucleotide polymorphism; Mathematics; Computer science; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001138068,0.000105074,0.00008950764,0.000006975959,0.0001202846,0.00001930028,0.0002621713,0.00006929805,0.00002283169],"category_scores_gemma":[0.00005725159,0.0000789355,0.00006561542,0.00004859998,0.00004456957,0.000001774736,0.00007308122,0.00007042779,0.00002617556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007624827,"about_ca_system_score_gemma":0.00005555897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003457362,"about_ca_topic_score_gemma":0.000004230707,"domain_scores_codex":[0.9993254,0.00002907693,0.0001287437,0.0002517171,0.00007178672,0.0001932866],"domain_scores_gemma":[0.999688,0.00003377391,0.00004569029,0.0001273465,0.00002898679,0.00007625388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003194874,0.00001874058,0.002896616,0.00002820076,0.00005817533,1.314905e-7,0.0004262074,0.001513797,0.9847841,0.0004655395,0.008974274,0.0005147922],"study_design_scores_gemma":[0.001547835,0.005291363,0.2471906,0.00003460418,0.000282415,0.0001590952,0.0004198705,0.002200004,0.08718394,0.002525562,0.6521515,0.001013269],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9588389,0.0014528,0.0362256,0.002529263,0.0001523649,0.0003822805,0.0001045818,0.00002190216,0.00029233],"genre_scores_gemma":[0.9927103,0.00007395082,0.004255565,0.001512673,0.0009885916,0.00003002399,0.00006730398,0.00001654034,0.0003450335],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8976001,"threshold_uncertainty_score":0.3218896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09785801795706675,"score_gpt":0.2774991185942078,"score_spread":0.1796411006371411,"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."}}