{"id":"W2091798987","doi":"10.2135/cropsci2011.05.0253","title":"Genomic Selection Accuracy for Grain Quality Traits in Biparental Wheat Populations","year":2011,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":302,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hatch; National Institute of Food and Agriculture","keywords":"Biology; Selection (genetic algorithm); Quantitative trait locus; Marker-assisted selection; Genomic selection; Genotyping; Trait; Population; Phenotypic trait; Plant breeding; Genetic marker; Genetic gain; Genetics; Evolutionary biology; Genetic variation; Phenotype; Genotype; Single-nucleotide polymorphism; Agronomy; Gene; Machine learning; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.004332335,0.000320283,0.0003215696,0.0005111514,0.0001644488,0.0004615163,0.0003687796,0.0002458662,0.0004204534],"category_scores_gemma":[0.006600156,0.0001246586,0.0002720265,0.0002642562,0.0002617897,0.0003764268,0.0003956668,0.000389832,0.0001600111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003091357,"about_ca_system_score_gemma":0.0001013506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001364248,"about_ca_topic_score_gemma":0.001866159,"domain_scores_codex":[0.9980577,0.001052113,0.0001175285,0.0004563015,0.0002467431,0.00006958506],"domain_scores_gemma":[0.9931999,0.004516426,0.0006760053,0.001027673,0.0004921525,0.00008778449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001388357,0.0002881121,0.6122171,0.00009470154,0.001118017,0.0001451725,0.0006609633,0.07199333,0.1706396,0.0006372807,0.0005068646,0.1403105],"study_design_scores_gemma":[0.00004784915,0.000409043,0.7785426,0.00001521311,0.0002155746,0.0001752023,0.0001180639,0.1872974,0.03200356,0.0006932135,0.000442155,0.00004015975],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895802,0.00006275162,0.009887933,0.00001657398,0.00000408602,0.000004438552,0.00009280087,0.00008468622,0.0002665102],"genre_scores_gemma":[0.9977652,0.00001023011,0.001954122,0.00000781674,0.000001077336,0.000003648903,0.0001610746,0.000009625873,0.00008732807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004332335,"threshold_uncertainty_score":0.02291185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07485954781574858,"score_gpt":0.3355050099535005,"score_spread":0.260645462137752,"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."}}