{"id":"W3210529686","doi":"10.1007/s00122-021-03982-0","title":"Genome-based prediction of agronomic traits in spring wheat under conventional and organic management systems","year":2021,"lang":"en","type":"article","venue":"Theoretical and Applied Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture Food and Rural Development; Agriculture and Agri-Food Canada; University of Saskatchewan; University of Alberta","funders":"Saskatchewan Wheat Development Commission; Alberta Wheat Commission; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Agriculture and Agri-Food Canada; Western Grains Research Foundation; Alberta Crop Industry Development Fund","keywords":"Biology; Organic farming; Predictive modelling; Selection (genetic algorithm); SNP; Biotechnology; Genotype; Cultivar; Agronomy; Agriculture; Genetics; Statistics; Single-nucleotide polymorphism; Machine learning; Ecology; Computer science; Mathematics; 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":[0.00009691283,0.0001104127,0.0001349405,0.00002522636,0.00002906221,0.00001321387,0.00005742647,0.0000959128,0.00003668553],"category_scores_gemma":[0.000002426242,0.0001103636,0.00002176762,0.00004679507,0.0002617808,7.471309e-7,0.00008093468,0.00005491501,0.000001314305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006574986,"about_ca_system_score_gemma":0.00002864614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.41057e-7,"about_ca_topic_score_gemma":0.000001681525,"domain_scores_codex":[0.999262,0.00003221998,0.0002085845,0.0002704151,0.00008121139,0.0001455866],"domain_scores_gemma":[0.9997458,0.00001392025,0.00003169869,0.0001222557,0.00002145276,0.000064915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00007291097,0.00008988292,0.001105632,0.0001212023,0.00004868231,5.677149e-7,0.00002694221,0.003818412,0.4312897,0.5622753,0.000003840615,0.001146973],"study_design_scores_gemma":[0.002907323,0.0003063696,0.8557782,0.00006149853,0.000114493,0.00001697131,0.0005848759,0.000654388,0.1039586,0.03488527,0.0004046542,0.0003274018],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9670771,0.0015931,0.02935205,0.00003955109,0.00004562395,0.0001739572,0.00002038262,0.000004460208,0.001693772],"genre_scores_gemma":[0.9939603,0.0001700687,0.005647708,0.00004835405,0.00005741189,0.00001388515,0.00003688146,0.00001301014,0.00005243787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8546726,"threshold_uncertainty_score":0.4500496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006025769362453255,"score_gpt":0.1919337275507645,"score_spread":0.1859079581883112,"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."}}