{"id":"W2992696371","doi":"10.5539/jas.v12n1p84","title":"Forage Production and Bromatological Composition of Forage Species Intercropped With Soybean","year":2019,"lang":"en","type":"article","venue":"Journal of Agricultural Science","topic":"Soil Management and Crop Yield","field":"Agricultural and Biological Sciences","cited_by":12,"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":"Monoculture; Forage; Agronomy; Biology; Intercropping; Pasture; Crop; Productivity; Livestock; Brachiaria; Ecology","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":[0.0003169486,0.00009489997,0.0001905057,0.00002572302,0.0001251498,0.00009255616,0.0002642913,0.0000321776,0.00006930422],"category_scores_gemma":[0.00003459724,0.00002524706,0.00005370408,0.0005180172,0.0002474063,0.0006640011,0.00007361233,0.000105985,0.000003434589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002283398,"about_ca_system_score_gemma":0.000006098531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001361893,"about_ca_topic_score_gemma":0.00003791251,"domain_scores_codex":[0.9989895,0.00002329834,0.0002440399,0.0001652618,0.0004075863,0.0001703467],"domain_scores_gemma":[0.9993122,0.00004284075,0.0003006824,0.00003291321,0.0002407162,0.00007064591],"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":[0.00006398132,0.00005623998,0.05376308,0.00001138054,0.000008166712,0.000003071698,0.0001098369,0.00001030763,0.9433802,0.0004028094,0.0002521497,0.001938808],"study_design_scores_gemma":[0.0001119787,0.0009234599,0.9589601,0.00009342501,0.00001376916,0.0001457121,0.001806512,0.000006903557,0.03764715,0.00006899027,0.0001304331,0.00009152106],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969686,0.00003939751,0.000003561129,0.001442073,0.0001586688,0.0001459298,0.000001248059,0.000009888025,0.001230669],"genre_scores_gemma":[0.9994425,0.00002432496,0.0001645712,0.00002941966,0.0001029932,6.436818e-7,0.000001556845,3.089533e-7,0.0002336625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.905733,"threshold_uncertainty_score":0.1029545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01229125984456464,"score_gpt":0.1995568338440236,"score_spread":0.187265573999459,"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."}}