{"id":"W2939763985","doi":"10.5539/jas.v11n5p395","title":"Macronutrient Fertilization on the Yield Components and Nutrition of Lima Bean","year":2019,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Agronomic Practices and Intercropping Systems","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Point of delivery; Nutrient; Human fertilization; Context (archaeology); Phosphorus; Crop; Population; Biology; Toxicology; Randomized block design; Agronomy; Horticulture; Animal science; Chemistry; Medicine","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":[0.0001729796,0.0003121661,0.0003098879,0.0003120352,0.0002426894,0.0003834564,0.0002309654,0.0002584954,0.0008628355],"category_scores_gemma":[0.0002807627,0.0001290956,0.0002544782,0.000258061,0.0002339457,0.0002118696,0.0002826818,0.0002670058,0.0001706292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004706111,"about_ca_system_score_gemma":0.0003359229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003144684,"about_ca_topic_score_gemma":0.005058318,"domain_scores_codex":[0.9998568,0.00003210439,0.00001524186,0.00003385174,0.0000330281,0.0000289348],"domain_scores_gemma":[0.9996504,0.00006323514,0.00007693628,0.00002024635,0.00005620052,0.0001328718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002111414,0.0001588099,0.003244927,0.0001727909,0.00003188611,0.0001073691,0.00007557297,0.00009150532,0.9905558,0.00003669382,0.00002575951,0.003387463],"study_design_scores_gemma":[0.00009187703,0.009885817,0.2305274,0.00006061823,0.000252449,0.0002947246,0.0004848027,0.00129433,0.7522681,0.0001777168,0.004621921,0.0000401961],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984101,0.0007436539,0.0001267071,0.00002889845,0.000005657904,0.000006310421,0.000087779,0.00001313659,0.0005777681],"genre_scores_gemma":[0.9979265,0.0003921766,0.0003270096,0.00004541489,0.000003491522,0.000007051501,0.0001595013,0.000009626033,0.001129217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003144684,"threshold_uncertainty_score":0.006252766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03555918718508719,"score_gpt":0.2246101255589325,"score_spread":0.1890509383738453,"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."}}