{"id":"W2337877257","doi":"10.1007/978-3-319-16988-0_2","title":"Precision Nitrogen Management for Sustainable Corn Production","year":2015,"lang":"en","type":"book-chapter","venue":"Sustainable agriculture reviews","topic":"Plant nutrient uptake and metabolism","field":"Agricultural and Biological Sciences","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Leaching (pedology); Agronomy; Environmental science; Cropping; Sowing; Fertilizer; Cropping system; Crop; Production (economics); Yield (engineering); Nitrogen; Soil water; Agriculture; Geography; Biology; Chemistry; Economics; Soil science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001577608,0.0007741395,0.001177083,0.00006544831,0.0005306306,0.0001954675,0.0006183574,0.0005799816,0.0002429894],"category_scores_gemma":[0.0002247471,0.000267205,0.0006278338,0.0003127092,0.00005010282,0.0004154883,0.0003085157,0.0003694209,0.0002141179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003811617,"about_ca_system_score_gemma":0.00004234648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003241517,"about_ca_topic_score_gemma":0.00002951867,"domain_scores_codex":[0.9963461,0.00008494938,0.0008280493,0.001093022,0.0005634457,0.001084428],"domain_scores_gemma":[0.9972049,0.00006873704,0.0007027236,0.0002669813,0.001448128,0.0003085437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007845978,0.00006738379,0.00000238656,0.0007008562,0.00007193334,0.00008122418,0.00002849687,0.000001483812,0.0001733385,0.1777931,0.7199439,0.1010575],"study_design_scores_gemma":[0.0002125678,0.0002001466,0.00001526423,0.0003300136,0.0003829179,0.00003281624,0.000794085,3.122678e-7,0.00006710008,0.06826077,0.9290441,0.0006598798],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003355182,0.297064,0.0000242162,0.00140664,0.0006711592,0.01918943,0.0001684616,0.0003159026,0.6808246],"genre_scores_gemma":[0.00006704538,0.07186547,0.0002118858,0.0001674934,0.001696988,0.0007509433,0.002161355,0.000008931127,0.9230699],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2422453,"threshold_uncertainty_score":0.999978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0319982479296901,"score_gpt":0.240409921915458,"score_spread":0.2084116739857679,"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."}}