{"id":"W2801914509","doi":"10.1038/s41598-018-24896-w","title":"Genomic analysis and immune response in a murine mastitis model of vB_EcoM-UFV13, a potential biocontrol agent for use in dairy cows","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Sistema de Laboratórios em Nanotecnologias, Universidade Federal de Viçosa; Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Ciência, Tecnologia e Inovação; Financiadora de Estudos e Projetos; Empresa Brasileira de Pesquisa Agropecuária; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Universidade Federal de Viçosa","keywords":"Mastitis; Immune system; Biology; Dairy cattle; Biological pest control; Genetics; Microbiology; Biotechnology; Virology; Botany","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":[],"consensus_categories":[],"category_scores_codex":[0.002250686,0.0001103525,0.0003393418,0.0001739999,0.0001256526,0.0000677015,0.0001125788,0.00005888341,0.0001023107],"category_scores_gemma":[0.000252464,0.00005406713,0.0001550605,0.0006739842,0.0002705246,0.000120012,0.0001355173,0.00003958824,0.000002328858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002646922,"about_ca_system_score_gemma":0.00001484365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007162502,"about_ca_topic_score_gemma":0.003596323,"domain_scores_codex":[0.9982763,0.0001231863,0.0006097369,0.0005756158,0.0001198833,0.0002952868],"domain_scores_gemma":[0.9993738,0.0001032747,0.0002491494,0.000141652,0.00006930733,0.00006281621],"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":[0.001875151,0.0002089142,0.3514303,0.00001940203,0.00009618001,0.00007319957,0.0001218379,0.001357159,0.6402263,0.00006070238,0.001282543,0.003248295],"study_design_scores_gemma":[0.0002475469,0.0001623346,0.9254732,0.00001313934,0.0000722476,0.000003333776,0.00007422001,0.0711294,0.0003548705,0.001621401,0.0007256038,0.0001226637],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983853,0.0001039684,0.0003681804,0.0003750334,0.0002534032,0.0004392302,0.00003870905,0.00001209852,0.00002410738],"genre_scores_gemma":[0.9985705,0.000009298758,0.0006075401,0.00004820987,0.00003101261,0.0000339596,0.00009167088,9.812831e-7,0.0006068157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6398714,"threshold_uncertainty_score":0.2204793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03463734173407709,"score_gpt":0.2482749732057428,"score_spread":0.2136376314716658,"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."}}