{"id":"W2920490422","doi":"10.11606/d.74.2018.tde-20062018-142234","title":"Uso combinado de monensina e nitrato como manipuladores da cinética e da fermentação ruminal para mitigação da produção de metano em bovinos","year":2018,"lang":"pt","type":"dissertation","venue":"","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo; Universidade de São Paulo","keywords":"Monensin; Chemistry; Fermentation; Biology; Food science; Biochemistry","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":[0.0002531228,0.0002615267,0.0004456305,0.0001732043,0.0001562233,0.0004408321,0.0003119046,0.0002892347,0.0008572731],"category_scores_gemma":[0.0002759613,0.0001649251,0.0002116994,0.0001440588,0.0002392444,0.0002715642,0.0002255944,0.0002905143,0.0001002738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002813782,"about_ca_system_score_gemma":0.0003086154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001807423,"about_ca_topic_score_gemma":0.005656354,"domain_scores_codex":[0.9998749,0.00002329962,0.00001050597,0.00004027134,0.0000279347,0.00002304337],"domain_scores_gemma":[0.9997593,0.00006145208,0.00007639496,0.00001811009,0.00003261891,0.00005208104],"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":[0.001769842,0.0002051872,0.001355369,0.0001106315,0.00002131523,0.00002114771,0.00003831513,0.000090899,0.9923021,0.00001470588,0.000007052916,0.004063488],"study_design_scores_gemma":[0.00007415467,0.02557437,0.03393435,0.00004221822,0.00017995,0.0001197581,0.0002303884,0.001111895,0.9363523,0.00003963071,0.002323775,0.00001721462],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988177,0.000577211,0.0003678917,0.00001910492,0.00000621052,0.00001817097,0.00002935905,0.000005448391,0.0001587847],"genre_scores_gemma":[0.9924931,0.0009796928,0.004027462,0.00003846069,0.000007687363,0.00003721437,0.00007780395,0.000006477776,0.002332105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001807423,"threshold_uncertainty_score":0.003593862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05538603949146808,"score_gpt":0.2997978070919964,"score_spread":0.2444117676005283,"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."}}