{"id":"W2792865085","doi":"10.5539/jas.v10n4p223","title":"Micronutrient Content and Physiological Quality of Soybean Seeds","year":2018,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Plant Micronutrient Interactions and Effects","field":"Agricultural and Biological Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Micronutrient; Molybdenum; Manganese; Zinc; Chemistry; Copper; Cultivar; Horticulture; Agronomy; Food science; Biology; Inorganic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001563611,0.0002091122,0.0001986714,0.0003324042,0.0001454846,0.0002878719,0.0000961378,0.0001565189,0.0007427927],"category_scores_gemma":[0.0002562873,0.0001334185,0.0001092853,0.0001932397,0.0001320254,0.0001385743,0.0001658083,0.0002633252,0.0001231881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002623379,"about_ca_system_score_gemma":0.0001773989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002276978,"about_ca_topic_score_gemma":0.003476557,"domain_scores_codex":[0.999873,0.00001955364,0.00001496784,0.00004841644,0.00002746472,0.00001656218],"domain_scores_gemma":[0.9997627,0.00003319405,0.00006567466,0.00001455328,0.00004982333,0.000074064],"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":[0.0003016162,0.00002598472,0.007987346,0.00004825915,0.00001445861,0.00003678136,0.0000394066,0.0000214988,0.9905971,0.00001882848,0.00001103594,0.0008977408],"study_design_scores_gemma":[0.00002246303,0.001177428,0.7308069,0.00001199679,0.00005768946,0.0003558288,0.0001531751,0.0004593762,0.2660311,0.0000802488,0.0008319446,0.00001169352],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983566,0.0004920759,0.0004056499,0.0000152554,0.000003318309,0.000009969801,0.0002850616,0.00001314372,0.0004188474],"genre_scores_gemma":[0.9984841,0.0001301298,0.0004173391,0.00001540949,9.587546e-7,0.0000106575,0.000386989,0.000006158415,0.0005483061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002276978,"threshold_uncertainty_score":0.00452739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06401217822029998,"score_gpt":0.2754274909428855,"score_spread":0.2114153127225856,"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."}}