{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007780024,0.0001049774,0.0002497827,0.0000237971,0.0002424228,0.00005907653,0.000331965,0.00004376566,0.00005316692],"category_scores_gemma":[0.0001652672,0.00002838521,0.0001048227,0.0004975213,0.000584381,0.0003893056,0.00009904295,0.0001231238,0.000005837656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004051182,"about_ca_system_score_gemma":0.00001378605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007280752,"about_ca_topic_score_gemma":0.00002971135,"domain_scores_codex":[0.9987596,0.00006548272,0.0004286143,0.0001666141,0.0003464654,0.0002332783],"domain_scores_gemma":[0.9985488,0.0001518169,0.0004806823,0.00003239356,0.0006308306,0.0001554744],"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":[0.00004676606,0.00009202397,0.002953867,0.000003507412,0.000006690388,8.80941e-7,0.00008640704,3.159776e-7,0.99403,0.0002233233,0.0006140221,0.001942193],"study_design_scores_gemma":[0.0001366149,0.0009534816,0.8072071,0.00004646686,0.000007172418,0.000126032,0.0007101119,0.000002316855,0.1899148,0.00006005801,0.0007521578,0.00008367542],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986947,0.0001264858,0.000002938576,0.0005598742,0.0002735321,0.00007948901,0.00001377862,0.000006503462,0.0002426524],"genre_scores_gemma":[0.9993619,0.00005223433,0.0001668843,0.00007505375,0.0002864725,5.67686e-7,0.000002055631,2.066346e-7,0.00005459538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8042532,"threshold_uncertainty_score":0.2153176,"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."}}