{"id":"W2605338866","doi":"10.1007/s00122-017-2897-1","title":"Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat","year":2017,"lang":"en","type":"article","venue":"Theoretical and Applied Genetics","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":147,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Consortium of International Agricultural Research Centers; Hatch; United States Agency for International Development","keywords":"Biology; Rust (programming language); Stem rust; Seedling; Reproducing kernel Hilbert space; Plant breeding; Marker-assisted selection; Plant disease resistance; Genetic marker; Agronomy; Genetics; Resistance (ecology); Gene; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002025167,0.0001218345,0.000168432,0.000008747277,0.0003225748,0.0001046301,0.0001038259,0.0001235354,0.00001581827],"category_scores_gemma":[0.000008174066,0.00005650267,0.00001819439,0.0000216576,0.0005757952,0.0000123141,0.00007116103,0.00007427551,6.767829e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003962575,"about_ca_system_score_gemma":0.000005376647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003851757,"about_ca_topic_score_gemma":0.0001573141,"domain_scores_codex":[0.9992585,0.00001919533,0.0001492068,0.0002924157,0.00006265703,0.0002180121],"domain_scores_gemma":[0.9996513,0.0001132187,0.00004246166,0.0000763728,0.00001700352,0.00009961709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0008282503,0.0001088437,0.03959207,0.0001000792,0.00001234112,0.000004205547,0.0001963362,0.000009606666,0.4680908,0.2542057,0.000152125,0.2366997],"study_design_scores_gemma":[0.001701534,0.0007587617,0.857172,0.00004307996,0.0000567233,0.00000598396,0.0001848388,0.001086748,0.01533392,0.1166001,0.00663454,0.000421814],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996172,0.001011546,0.00006558972,0.001244529,0.00004225166,0.0002906144,0.00009499785,0.00001060698,0.001067865],"genre_scores_gemma":[0.99845,0.000596165,0.0005630684,0.0001151291,0.0001635453,0.00002481852,0.00001602204,0.000001667423,0.00006961431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8175799,"threshold_uncertainty_score":0.2481017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01592910697610793,"score_gpt":0.2162545097403181,"score_spread":0.2003254027642102,"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."}}