{"id":"W3016509734","doi":"10.2134/csa2016-61-7-1","title":"G×E: Bringing genotype by environment interactions to the fore to tackle the formidable challenges ahead","year":2016,"lang":"en","type":"article","venue":"CSA News","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genotype; Computer science; Biology; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001147379,0.00006922405,0.0000540814,0.000003954272,0.0002526605,0.00004222059,0.0002367889,0.00002020706,0.0005330631],"category_scores_gemma":[0.00001624332,0.00001536564,0.00003285324,0.00005394281,0.000009656948,0.00003283599,0.000101883,0.00004072946,0.0003254784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001789034,"about_ca_system_score_gemma":0.0000014264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001962941,"about_ca_topic_score_gemma":0.002421091,"domain_scores_codex":[0.9994632,0.00001520166,0.00008100062,0.000149295,0.00009209271,0.0001992135],"domain_scores_gemma":[0.9997064,0.0001251115,0.00002270063,0.00006752607,0.000008075002,0.00007016336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007738378,0.00001428436,0.0005240695,9.038575e-7,0.000006659228,3.281499e-7,0.0003193145,0.00001733922,0.257925,0.0001290577,0.05861137,0.6824439],"study_design_scores_gemma":[0.00002121074,0.00008092295,0.01184809,0.00001237544,0.000003240216,0.000002860685,0.0003984813,0.00001820095,0.001954262,0.0001070543,0.9854884,0.0000649089],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8416303,0.000668346,0.0001178915,0.1507589,0.00024285,0.0003640695,0.00005676992,0.00002223203,0.006138616],"genre_scores_gemma":[0.9927313,0.0004207947,0.00007416892,0.0009744641,0.0003176002,0.00003796399,0.000004219413,8.979061e-7,0.005438561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.926877,"threshold_uncertainty_score":0.5836668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04090410290191288,"score_gpt":0.2075550979530282,"score_spread":0.1666509950511153,"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."}}