{"id":"W2017861737","doi":"10.1046/j.1344-3941.2002.00001.x","title":"Genetic improvement in the presence of genotype by environment interaction","year":2002,"lang":"en","type":"article","venue":"Animal Science Journal","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Gene–environment interaction; Selection (genetic algorithm); Index selection; Profitability index; Interaction; Main effect; Breed; Genetic gain; Computer science; Genotype; Biology; Statistics; Genetics; Mathematics; Artificial intelligence; Economics; Genetic variation; 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":[0.001677065,0.0004516093,0.0007340848,0.0007621878,0.0002488469,0.0007992697,0.0006453859,0.0005601515,0.001708141],"category_scores_gemma":[0.001337706,0.0001556492,0.0004706678,0.0009328835,0.0004411343,0.0005168474,0.001015781,0.0008863815,0.0001981899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005474117,"about_ca_system_score_gemma":0.0003559371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002667913,"about_ca_topic_score_gemma":0.0007062972,"domain_scores_codex":[0.9985706,0.0006650768,0.00008569896,0.0001970293,0.0003191612,0.0001624166],"domain_scores_gemma":[0.9979918,0.001089841,0.0004104083,0.0001838748,0.0001671596,0.0001568421],"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":[0.0008232124,0.000572185,0.01638919,0.0002823073,0.0003268226,0.00190642,0.0002223056,0.009070891,0.8988507,0.005358958,0.0003178666,0.06587911],"study_design_scores_gemma":[0.0001795823,0.009472013,0.4681282,0.0001963851,0.001508955,0.005543139,0.000888865,0.09902596,0.3627133,0.01761541,0.03443614,0.0002920403],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9576303,0.0008566567,0.03619606,0.000260031,0.000047277,0.00005599653,0.0000975987,0.0001721546,0.004683925],"genre_scores_gemma":[0.9767774,0.000543947,0.02023473,0.0001570834,0.00002795166,0.00003400667,0.00018173,0.00005820789,0.001985108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001708141,"threshold_uncertainty_score":0.00886929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01183771784199775,"score_gpt":0.2351211791709742,"score_spread":0.2232834613289765,"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."}}