{"id":"W1925794974","doi":"10.2135/cropsci2014.09.0609","title":"Genetic Improvement Estimates, from Cultivar × Crop Management Trials, Are Larger in High‐Yield Cropping Environments","year":2015,"lang":"en","type":"article","venue":"Crop Science","topic":"Genetics and Plant Breeding","field":"Agricultural and Biological Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Cultivar; Biology; Agronomy; Adaptability; Genetic gain; Cropping; Yield (engineering); Crop yield; Crop; Genetic variation; Agriculture; Ecology","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":[0.001154869,0.0001703063,0.0002474293,0.00003609005,0.0002377999,0.0002540557,0.0006007109,0.00005780753,0.000190667],"category_scores_gemma":[0.0001729694,0.00007288391,0.00004604852,0.0004215238,0.0001573726,0.0001302559,0.0003171596,0.00009658784,0.00008816334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009395822,"about_ca_system_score_gemma":0.00001576616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001884737,"about_ca_topic_score_gemma":0.0002681948,"domain_scores_codex":[0.9979738,0.00003949321,0.0003762066,0.0005692047,0.000560428,0.000480879],"domain_scores_gemma":[0.9993603,0.0001027779,0.0001744065,0.0001142116,0.00002772147,0.0002205951],"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":[0.00002224576,0.0001171352,0.06465659,0.000004949887,0.000009893274,0.00004671147,0.0001379661,0.0006188304,0.8942251,0.00006603391,0.0005442359,0.03955025],"study_design_scores_gemma":[0.0003574079,0.0001285277,0.9701838,0.0000774558,0.00001633839,0.000001853634,0.0005004657,0.001174772,0.02057024,0.0007444929,0.005963917,0.000280738],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980426,0.0002832872,0.00008907126,0.0003720544,0.0004201034,0.0002996305,0.00005729325,0.00001991426,0.000415995],"genre_scores_gemma":[0.9972794,0.00007136921,0.002062591,0.0002119039,0.0001445017,0.00001939394,0.00001542427,0.000001247419,0.0001941852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9055272,"threshold_uncertainty_score":0.2972119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08580642919528055,"score_gpt":0.2466519219390067,"score_spread":0.1608454927437262,"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."}}