{"id":"W2987632096","doi":"10.5539/jas.v11n18p230","title":"Dry Mass Increment, Foliar Nutrientes and Soybean Yield as Affected by Aminoacid Application","year":2019,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Growth and nutrition in plants","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Glycine; Amino acid; Dry weight; Phenylalanine; Crop; Agronomy; Chemistry; Productivity; Yield (engineering); Nutrient; Crop yield; Dry matter; Horticulture; Biology; Biochemistry","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":[0.0003466464,0.0001227911,0.0001707893,0.00002591722,0.0002244062,0.000139397,0.0004017216,0.0000537936,0.00007016357],"category_scores_gemma":[0.00009063358,0.0000398521,0.00006037249,0.0006867966,0.0001208824,0.0006374774,0.00005271742,0.0001515119,0.00003944033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004115941,"about_ca_system_score_gemma":0.00001072783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007024117,"about_ca_topic_score_gemma":0.00002582071,"domain_scores_codex":[0.9986604,0.0000305034,0.0002759929,0.0002212047,0.000535274,0.0002765599],"domain_scores_gemma":[0.9990616,0.0001174938,0.0003046966,0.00003682657,0.0002478632,0.0002315067],"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":[0.00001677864,0.0000520967,0.07207031,0.000004926498,0.000004143875,9.234973e-7,0.00002382906,4.083794e-7,0.9245766,0.0001335771,0.00139587,0.001720558],"study_design_scores_gemma":[0.0002073651,0.0004935215,0.9093341,0.00004310297,0.000009704284,0.00005257753,0.0004333159,0.000007335701,0.08749303,0.0002328448,0.001553934,0.0001391567],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980332,0.0002254381,0.000008240208,0.0008217328,0.0001601927,0.0002022102,0.0000184731,0.00001641304,0.0005141612],"genre_scores_gemma":[0.9992812,0.0001375972,0.000103402,0.0001490606,0.0001449085,0.000003150057,0.00001162055,4.169235e-7,0.000168599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8372638,"threshold_uncertainty_score":0.1725974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005880648198882562,"score_gpt":0.1944133386291818,"score_spread":0.1885326904302992,"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."}}