{"id":"W2067823209","doi":"10.2135/cropsci2001.413656x","title":"Two Types of GGE Biplots for Analyzing Multi‐Environment Trial Data","year":2001,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":357,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Biplot; Principal component analysis; Gene–environment interaction; Statistics; Biology; Representativeness heuristic; Regression; Regression analysis; Main effect; Genotype; Mathematics; Genetics","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":[0.004658799,0.001361288,0.001228907,0.003755681,0.0005377646,0.00119641,0.0007666792,0.0006175287,0.01115119],"category_scores_gemma":[0.02114468,0.0006070472,0.00104265,0.004084497,0.0005409489,0.001001937,0.0008635926,0.001927463,0.003156403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000347063,"about_ca_system_score_gemma":0.0005508796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001157437,"about_ca_topic_score_gemma":0.002206064,"domain_scores_codex":[0.9953336,0.002875955,0.0003912938,0.0003537802,0.0008294987,0.0002157981],"domain_scores_gemma":[0.9837911,0.009276882,0.001242716,0.00322324,0.002074161,0.0003920392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.005278653,0.001266659,0.01819858,0.001306267,0.0004919737,0.0004337605,0.001486932,0.01495884,0.04659181,0.01527536,0.0562606,0.8384506],"study_design_scores_gemma":[0.003296223,0.004424893,0.324258,0.000541534,0.0004310594,0.002326084,0.001209088,0.3117638,0.09135276,0.032843,0.2261196,0.001433948],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05935725,0.0001934668,0.906237,0.0002489385,0.0003715255,0.001462662,0.00772139,0.01943505,0.004972808],"genre_scores_gemma":[0.099705,0.000122638,0.8799886,0.0001862683,0.00009537728,0.005373555,0.006925216,0.004475091,0.003128233],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01115119,"threshold_uncertainty_score":0.03730446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1763776359121647,"score_gpt":0.3042983420989384,"score_spread":0.1279207061867737,"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."}}