{"id":"W2950511618","doi":"10.1093/bioinformatics/bty387","title":"Indexed variation graphs for efficient and accurate resistome profiling","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science and Technology Facilities Council; Department for Business, Energy and Industrial Strategy, UK Government; Public Health Agency of Canada; World Health Organization","keywords":"Resistome; Metagenomics; Profiling (computer programming); Computer science; Workflow; Data mining; Computational biology; Biology; Bioinformatics; Genome; Gene; Genetics; Database","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006054063,0.0009813359,0.0007947558,0.003212312,0.0006408558,0.001460838,0.001342173,0.0008160826,0.003730942],"category_scores_gemma":[0.005221146,0.0005196968,0.001165804,0.003366667,0.0005534785,0.001979724,0.001305211,0.001262575,0.001998035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008333609,"about_ca_system_score_gemma":0.0008537812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003668854,"about_ca_topic_score_gemma":0.005699129,"domain_scores_codex":[0.998942,0.0002028867,0.00005980469,0.0002498626,0.0004435602,0.0001019192],"domain_scores_gemma":[0.9980883,0.0007161215,0.0002430055,0.0004477239,0.0004113799,0.00009337157],"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":[0.0005349218,0.0002583316,0.01059111,0.001138231,0.0002664765,0.0008386995,0.0006793395,0.2124258,0.1194789,0.05509308,0.03088391,0.5678111],"study_design_scores_gemma":[0.00003707545,0.0001029325,0.002647312,0.00006973732,0.00004949712,0.0004238739,0.0001647,0.8740317,0.02515978,0.07073129,0.02650349,0.00007856384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02240777,0.0004690783,0.9599869,0.0001981089,0.00006354863,0.000110505,0.002836644,0.01171303,0.002214535],"genre_scores_gemma":[0.2017096,0.0005437356,0.7810051,0.0002462842,0.00008089088,0.0002033973,0.0109914,0.002649808,0.00256977],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003730942,"threshold_uncertainty_score":0.01248127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506174008485551,"score_gpt":0.2494737906952323,"score_spread":0.2344120506103768,"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."}}