{"id":"W4393054540","doi":"10.1002/csc2.21231","title":"Two types of biplots to integrate multi‐trial and multi‐trait information for genotype selection","year":2024,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Biplot; Biology; Selection (genetic algorithm); Trait; Genotype; Evolutionary biology; Genetics; Computational biology; Biotechnology; Artificial intelligence; Gene; Computer science","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":[0.0003282458,0.00004978152,0.00005539634,0.00003336653,0.0001445906,0.0001686039,0.0001119898,0.00002211922,0.0000134811],"category_scores_gemma":[0.00009955253,0.00001969707,0.00001794077,0.0004902632,0.00006155358,0.0002023581,0.00003229921,0.00003218433,0.00001030348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008290437,"about_ca_system_score_gemma":0.00002044801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002195212,"about_ca_topic_score_gemma":0.0003037437,"domain_scores_codex":[0.9995236,0.000005217482,0.0001100486,0.000129997,0.0001031052,0.000127989],"domain_scores_gemma":[0.9997489,0.00004859494,0.00002477433,0.00001503233,0.0001084292,0.00005422955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001242119,0.000009434827,0.0004012167,0.00001231222,0.000001846142,7.573743e-8,0.000251132,0.00009092535,0.8478428,0.0007463941,0.00006490923,0.1504548],"study_design_scores_gemma":[0.004303476,0.003362902,0.2291988,0.0002574912,0.00005019524,0.00002467882,0.0008398989,0.4059594,0.2759062,0.0007731976,0.07854709,0.0007766844],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979166,0.00007511228,0.001140085,0.0001456634,0.0003274705,0.0002512398,0.00004270471,0.00002187253,0.00007921481],"genre_scores_gemma":[0.9953606,0.00001160845,0.004431611,0.00003816389,0.00007634714,0.000007675116,0.000006211993,2.826526e-7,0.00006751541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5719365,"threshold_uncertainty_score":0.1625851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04678210395958533,"score_gpt":0.2764077286261661,"score_spread":0.2296256246665808,"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."}}