{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003302953,0.0002055753,0.0001750475,0.0002453031,0.0001197074,0.0003672585,0.0001356855,0.000212916,0.0004202188],"category_scores_gemma":[0.0004633871,0.00006190062,0.0002325806,0.0002833309,0.0001308741,0.0001786947,0.0001381879,0.0001629491,0.00007968349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004775877,"about_ca_system_score_gemma":0.0002267297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007405614,"about_ca_topic_score_gemma":0.009978331,"domain_scores_codex":[0.999905,0.00003064224,0.000003787883,0.00003621394,0.00001059589,0.00001367792],"domain_scores_gemma":[0.9997435,0.0001635092,0.00003221693,0.00001019218,0.00003075404,0.00001988457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003888606,0.0006739616,0.5967915,0.0001292164,0.0006154699,0.0002969142,0.0002421511,0.1508126,0.1860113,0.0006576476,0.0006975412,0.05918296],"study_design_scores_gemma":[0.0000666117,0.0004633011,0.7639773,0.000003995508,0.0001183948,0.0000530304,0.0001437367,0.2274586,0.007100029,0.0003470258,0.0002526443,0.00001533395],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986132,0.00001590327,0.001052438,0.00001107708,0.000001594919,0.000002132907,0.0001837924,0.00001189751,0.0001079118],"genre_scores_gemma":[0.9987459,0.000008668506,0.0006922244,0.000005270994,7.989432e-7,0.000001769589,0.000447756,0.000001935875,0.0000956083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007405614,"threshold_uncertainty_score":0.01472503,"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."}}