{"id":"W2999009349","doi":"10.1002/csc2.20035","title":"Relative utility of agronomic, phenological, and morphological traits for assessing genotype‐by‐environment interaction in maize inbreds","year":2020,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Agricultural Research Service; National Institute of Food and Agriculture; Nebraska Corn Board; National Science Foundation; Iowa State University; University of Wisconsin-Madison; U.S. Department of Agriculture","keywords":"Biology; Trait; Gene–environment interaction; Quantitative trait locus; Phenology; Variance components; Agronomy; Sowing; Genotype; Growing season; Phenotypic trait; Yield (engineering); Phenotype; Genetics; Statistics; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001627886,0.0005221758,0.0002968122,0.002423846,0.0002945511,0.0006387049,0.0003034431,0.0003640943,0.00055417],"category_scores_gemma":[0.001669844,0.0002242431,0.0005727491,0.0009616127,0.0003373708,0.0004274794,0.0006096148,0.0005105338,0.0001435077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002521911,"about_ca_system_score_gemma":0.000155938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001435442,"about_ca_topic_score_gemma":0.002451373,"domain_scores_codex":[0.9993844,0.000246341,0.00005972293,0.0001431546,0.0001094346,0.00005685887],"domain_scores_gemma":[0.9976711,0.0009198894,0.000737277,0.0002105939,0.0002050959,0.0002561983],"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":[0.0008735572,0.000253287,0.4557332,0.00004699237,0.0004297305,0.0000999861,0.0002694948,0.001012897,0.5324534,0.0001321625,0.00004697507,0.008648337],"study_design_scores_gemma":[0.000007066218,0.000181745,0.9879912,0.000002550441,0.00004856626,0.0000471767,0.00007724228,0.001153086,0.01035512,0.0000455929,0.0000751047,0.00001559301],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985664,0.00005551232,0.0009733437,0.000005115597,0.00000131646,0.00000838799,0.0002310178,0.00001440104,0.0001445044],"genre_scores_gemma":[0.9978065,0.00002672697,0.00171165,0.00001045721,0.00000235082,0.00001137515,0.0003150657,0.00001280578,0.0001030339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002423846,"threshold_uncertainty_score":0.008609235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0803872867027248,"score_gpt":0.2522048701880948,"score_spread":0.17181758348537,"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."}}