{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001283606,0.0002763749,0.0001703751,0.0002915529,0.0001140335,0.0001649162,0.0001324516,0.000342239,0.0007516769],"category_scores_gemma":[0.00009832389,0.0000998925,0.000285242,0.0001486099,0.0001434868,0.0001416778,0.00009904906,0.000559044,0.0001714821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001626502,"about_ca_system_score_gemma":0.00009710911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005234128,"about_ca_topic_score_gemma":0.0006203782,"domain_scores_codex":[0.9998366,0.00002069607,0.00001100558,0.00004571921,0.00004345351,0.00004252511],"domain_scores_gemma":[0.9999274,0.00001159422,0.00002620386,0.000006622848,0.00001038033,0.00001772516],"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":[0.0001071498,0.00004015381,0.0003473934,0.00001735816,0.000003651942,0.00001807337,0.00001336201,0.00002447018,0.9988533,0.00001674227,0.00001330343,0.0005450555],"study_design_scores_gemma":[0.00002817816,0.003080565,0.03606952,0.00001575222,0.00005623871,0.0003819687,0.0001243256,0.001167556,0.9565434,0.00007291335,0.00244991,0.000009628679],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967103,0.0007276408,0.001325274,0.00004010416,0.0000183595,0.00002262269,0.0007745884,0.00002679316,0.0003543399],"genre_scores_gemma":[0.9915624,0.0005835771,0.002440915,0.00007964069,0.000009243738,0.00006419884,0.002216567,0.00001657057,0.003026956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007516769,"threshold_uncertainty_score":0.002514601,"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."}}