{"id":"W2340057483","doi":"10.1186/s12866-016-0680-0","title":"SuperPhy: predictive genomics for the bacterial pathogen Escherichia coli","year":2016,"lang":"en","type":"article","venue":"BMC Microbiology","topic":"Escherichia coli research studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"Public Health Agency; Public Health Agency of Canada; Oxford Nanopore Technologies","keywords":"Biology; Genomics; Genome; Whole genome sequencing; Comparative genomics; Computational biology; Genetics; Context (archaeology); Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001389772,0.0009106593,0.0005224598,0.000835632,0.0003488443,0.001140895,0.001306682,0.0006373443,0.002961218],"category_scores_gemma":[0.002670998,0.0003992205,0.000667021,0.000549303,0.0005488691,0.001070374,0.001711202,0.00119358,0.001134893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000450748,"about_ca_system_score_gemma":0.0007590026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001490758,"about_ca_topic_score_gemma":0.0009757971,"domain_scores_codex":[0.9995095,0.000106422,0.00001818312,0.0001410173,0.0001754745,0.00004931559],"domain_scores_gemma":[0.9988391,0.0006905001,0.0001060006,0.0001305522,0.0001282312,0.0001056521],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00461062,0.0007398648,0.04513322,0.001795595,0.0006097831,0.002384806,0.001281181,0.1601138,0.2485893,0.04694825,0.09481578,0.3929777],"study_design_scores_gemma":[0.0002300603,0.0006884558,0.01666654,0.0001875773,0.0001592958,0.0009821929,0.0002158283,0.7672777,0.09915596,0.0383679,0.07583056,0.0002380491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1423764,0.001082368,0.700929,0.001963853,0.0002056648,0.0006191953,0.01803972,0.1265319,0.008251867],"genre_scores_gemma":[0.5066456,0.001163657,0.4550086,0.0008945597,0.0001205918,0.0007776599,0.02749402,0.004233121,0.003662193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002961218,"threshold_uncertainty_score":0.009906292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01609826859124033,"score_gpt":0.2526561810989851,"score_spread":0.2365579125077448,"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."}}