{"id":"W2612132372","doi":"10.1371/journal.pone.0177509","title":"Estimating nutrient uptake requirements for soybean using QUEFTS model in China","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Plant Biotechnology Institute","funders":"Chinese Academy of Agricultural Sciences; International Plant Nutrition Institute","keywords":"Nutrient; Fertilizer; Yield (engineering); Phosphorus; Sowing; Agronomy; Potash; Soil fertility; Animal science; Nitrogen; Nutrient management; Field experiment; Mathematics; Potassium; Crop yield; Soil water; Environmental science; Biology; Chemistry; Ecology; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004076252,0.0009428728,0.0005243822,0.0006328459,0.0003271832,0.0006270231,0.001085589,0.0008785115,0.001122795],"category_scores_gemma":[0.000860182,0.0003206163,0.0008626818,0.0005062652,0.0003808687,0.0005829259,0.0003930891,0.0003097689,0.0001473793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00220706,"about_ca_system_score_gemma":0.001480046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2313352,"about_ca_topic_score_gemma":0.1112971,"domain_scores_codex":[0.9998658,0.00002009554,0.000008184128,0.00005050919,0.00001951635,0.00003587395],"domain_scores_gemma":[0.9996668,0.0001625788,0.00005082594,0.000012983,0.00008241938,0.00002427828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004601589,0.00002093698,0.01507367,0.00003254835,0.00002584428,0.00008723932,0.00002060208,0.980906,0.00129217,0.0005103056,0.0002983546,0.001686376],"study_design_scores_gemma":[0.00001202138,0.0000116702,0.00274358,0.000002046558,0.00001062479,0.000008629951,0.00001130229,0.9966306,0.0001882209,0.0002293128,0.0001456289,0.000006372126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847269,0.000301381,0.008642285,0.0002404526,0.00001048863,0.00002528307,0.001800637,0.0001648014,0.004087835],"genre_scores_gemma":[0.9952675,0.0001528049,0.001834239,0.00003941439,0.000004111596,0.00002970445,0.001299194,0.00001832983,0.001354747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2313352,"threshold_uncertainty_score":0.4599773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.164465360541496,"score_gpt":0.2895624920252356,"score_spread":0.1250971314837396,"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."}}