{"id":"W2904663000","doi":"10.5539/jas.v11n1p350","title":"Does the Nitrogen Rates, Methods and Times of Application Influences the Corn Nutrition and Yield?","year":2018,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Crop Yield and Soil Fertility","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Randomized block design; Urea; Nitrogen; Sowing; Oxisol; Nutrient; Agronomy; Context (archaeology); Human fertilization; Chemistry; Yield (engineering); Leaf area index; Micronutrient; Chlorophyll; Animal science; Mathematics; Horticulture; Biology; Soil water; Materials science","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":[0.001182727,0.00006585348,0.0001095352,0.000007138521,0.0004691899,0.0001084705,0.0003330371,0.00003011299,0.00002262713],"category_scores_gemma":[0.0001985347,0.00001061532,0.0000389526,0.0003923924,0.001010358,0.000291358,0.00007393677,0.00009178571,5.23712e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008506187,"about_ca_system_score_gemma":0.000009807864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001671181,"about_ca_topic_score_gemma":0.000193997,"domain_scores_codex":[0.9992356,0.00007695455,0.0002234073,0.0001167737,0.0002297577,0.0001174982],"domain_scores_gemma":[0.99892,0.0003930004,0.0002395147,0.00003783184,0.0003530144,0.00005662147],"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":[0.00001537478,0.00002106455,0.01501271,0.000003493304,0.000004581574,8.939919e-8,0.0002945405,2.126495e-7,0.9337749,0.0002248535,0.0001177525,0.05053039],"study_design_scores_gemma":[0.00003703858,0.000162639,0.8989307,0.00001996879,0.00001249849,0.00003437882,0.001700534,0.00002017759,0.09524487,0.002744279,0.001049558,0.00004336302],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943805,0.0004006135,0.000006536623,0.004894981,0.00008422651,0.0001174244,0.000002545388,0.000004013095,0.0001092001],"genre_scores_gemma":[0.9992114,0.0001590732,0.0002771085,0.00009306334,0.0002368033,0.000002354965,2.979357e-7,1.417867e-7,0.00001978717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.883918,"threshold_uncertainty_score":0.3722708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01983864474421855,"score_gpt":0.2910730243125594,"score_spread":0.2712343795683409,"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."}}