{"id":"W4406038282","doi":"10.5376/lgg.2024.15.0027","title":"The Role of Plant Density and Nutrient Management in Soybean Yield Optimization","year":2024,"lang":"en","type":"article","venue":"Legume Genomics and Genetics","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Yield (engineering); Nutrient; Nutrient management; Agronomy; Environmental science; Biology; Materials science; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001066464,0.00005617218,0.00005323282,0.000008286485,0.00007606671,0.00007004324,0.00005211317,0.00003386317,0.000003807776],"category_scores_gemma":[0.000002465943,0.00002299907,0.00001388723,0.00007819854,0.00003145781,0.00001060388,0.00006108957,0.00003511002,4.894209e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000776517,"about_ca_system_score_gemma":0.000002374551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000227873,"about_ca_topic_score_gemma":0.0001286974,"domain_scores_codex":[0.9995871,0.00001050014,0.0001209352,0.0001325062,0.00005725456,0.0000916803],"domain_scores_gemma":[0.9998608,0.00004825899,0.00002252538,0.00003102467,0.0000121847,0.00002521532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00006193419,0.00008246936,0.01943513,0.00005520445,0.00007616323,0.000007870918,0.001283996,0.002044786,0.232678,0.0291697,0.0001775523,0.7149272],"study_design_scores_gemma":[0.0004761241,0.0006039336,0.3695559,0.0001560681,0.0001067547,0.00002483859,0.007351729,0.3226588,0.08274398,0.04863345,0.1669703,0.0007180577],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939721,0.005252935,0.00006306057,0.0002683823,0.00005544205,0.000139657,0.00001434957,0.000005847262,0.0002282393],"genre_scores_gemma":[0.9940866,0.005346816,0.0004329505,0.00002844233,0.0000417121,0.000003883212,0.000015378,7.908584e-7,0.00004338945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7142091,"threshold_uncertainty_score":0.09378748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008737159429527479,"score_gpt":0.1811943262253742,"score_spread":0.1724571667958467,"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."}}