{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006998949,0.00005516235,0.00008462263,0.00001236752,0.0002094029,0.0000560026,0.0006875381,0.00001792601,0.00006247857],"category_scores_gemma":[0.0001113105,0.00002111125,0.00002373816,0.0002631047,0.0001594075,0.0001063205,0.0001904415,0.00002632048,0.000008206461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007533191,"about_ca_system_score_gemma":0.00001075654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001177514,"about_ca_topic_score_gemma":0.00009483524,"domain_scores_codex":[0.9991685,0.000008466932,0.0001291831,0.0002817208,0.0002140063,0.0001981407],"domain_scores_gemma":[0.9996603,0.00007693416,0.00006535817,0.00009910348,0.00003745656,0.00006086524],"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":[0.0001793722,0.00005841114,0.006535718,0.000001836016,0.000002503491,7.053464e-7,0.00002456221,0.0001119853,0.941765,0.00009696357,0.0001021262,0.05112078],"study_design_scores_gemma":[0.01786344,0.003017262,0.4924873,0.0001159674,0.0001291425,0.00003284965,0.0006329576,0.1267133,0.1035597,0.001230783,0.2528164,0.0014008],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989075,0.0001010227,0.000155696,0.0002335017,0.0001513115,0.0001705349,0.00008218022,0.000008328424,0.0001899271],"genre_scores_gemma":[0.9976251,0.00005978025,0.001948042,0.00002152444,0.0001441235,0.000002802856,0.00002720698,3.317451e-7,0.0001710602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8382053,"threshold_uncertainty_score":0.1610579,"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."}}