{"id":"W3042615076","doi":"10.1002/csc2.20268","title":"Testing for nonlinear genotype × environment interactions","year":2020,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Ministry of Agriculture and Forestry; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Function (biology); Nonlinear regression; Crossover; Hordeum vulgare; Nonlinear system; Range (aeronautics); Gene–environment interaction; Intersection (aeronautics); Statistics; Genotype; Mathematics; Regression analysis; Genetics; Ecology; Physics; Computer science; Poaceae","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":[0.0001085048,0.00004333414,0.000041252,0.000003544448,0.0003336305,0.00007607645,0.00020989,0.00001020129,0.00009488354],"category_scores_gemma":[0.0001344086,0.00001704282,0.00001846547,0.0002192667,0.00007504073,0.00006014692,0.0000622735,0.00003570009,0.00005210699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008414525,"about_ca_system_score_gemma":0.000008179241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000141222,"about_ca_topic_score_gemma":0.000007945121,"domain_scores_codex":[0.9994737,0.000003143407,0.00006969328,0.0001905218,0.0001063429,0.0001566235],"domain_scores_gemma":[0.999734,0.00008869213,0.00002827162,0.00001848078,0.00003081626,0.00009971878],"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":[0.000002098081,0.000005646355,0.001163894,0.000001039631,3.917527e-7,2.81282e-7,0.00004499459,0.00004408806,0.9434524,0.00002847927,0.0001044824,0.05515224],"study_design_scores_gemma":[0.000160348,0.001061243,0.2327176,0.00002160647,0.00001544608,0.00001577112,0.0004591169,0.07671124,0.1220207,0.000350149,0.5660135,0.0004532355],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962805,0.00002232655,0.0001247212,0.002265182,0.00009364292,0.00009478672,0.00003631667,0.00002112559,0.001061419],"genre_scores_gemma":[0.9921315,0.000002040827,0.007173867,0.0003839875,0.000256371,0.000003789374,0.00000620636,2.6716e-7,0.00004201134],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8214316,"threshold_uncertainty_score":0.256605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09809233661928929,"score_gpt":0.2423704774134081,"score_spread":0.1442781407941188,"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."}}