{"id":"W2734410487","doi":"10.1186/s12864-017-3921-1","title":"Plasmid composition in Aeromonas salmonicida subsp. salmonicida 01-B526 unravels unsuspected type three secretion system loss patterns","year":2017,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Montréal; Fonds de recherche du Québec – Nature et technologies; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation; Université Laval","keywords":"Aeromonas salmonicida; Biology; Plasmid; Secretion; Microbiology; Composition (language); Zoology; Bacteria; Genetics; Gene; Biochemistry","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002539112,0.0003564577,0.0004306013,0.0001419654,0.0005413376,0.0001292652,0.000673343,0.0003892933,0.000210314],"category_scores_gemma":[0.00001823086,0.0003219247,0.0001417201,0.00007219736,0.0002122108,0.0001586116,0.000328546,0.000328428,0.001255911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005118061,"about_ca_system_score_gemma":0.00007549595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001046984,"about_ca_topic_score_gemma":0.006568722,"domain_scores_codex":[0.998184,0.000142018,0.0004686023,0.0005581528,0.00005407956,0.0005931475],"domain_scores_gemma":[0.9986795,0.00003772166,0.00030206,0.0008454025,0.00008906394,0.00004628678],"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":[0.0009948005,0.0002690164,0.1347235,0.0002937459,0.0002976493,0.00009896445,0.0008889114,0.0001846317,0.8558407,0.005356503,0.0007401349,0.0003114607],"study_design_scores_gemma":[0.008345133,0.0003821458,0.6884688,0.0005395412,0.0005010281,0.0002064659,0.002468997,0.0005077576,0.2880828,0.0003144692,0.008517409,0.001665484],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994541,0.0005946879,0.0009983483,0.0001398655,0.001195081,0.0007234833,0.0001346015,0.0001407131,0.00153223],"genre_scores_gemma":[0.9972093,0.00005307114,0.00008623729,0.0000548283,0.00009182873,0.00002211106,0.001901833,0.00004754508,0.0005332704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5677578,"threshold_uncertainty_score":0.9999233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940167734372538,"score_gpt":0.2381538743423794,"score_spread":0.218752196998654,"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."}}