{"id":"W2782174056","doi":"10.1016/j.cmi.2017.12.015","title":"A primer on microbial bioinformatics for nonbioinformaticians","year":2018,"lang":"en","type":"review","venue":"Clinical Microbiology and Infection","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Agency of Canada; University of Manitoba","funders":"Merck Sharp and Dohme; Fundació Catalana de Trasplantament; Türkiye Bilimsel ve Teknolojik Araştırma Kurumu; GlaxoSmithKline; Pfizer","keywords":"Bottleneck; Computer science; Raw data; Context (archaeology); Data science; Software deployment; Software; Field (mathematics); Biology; Software engineering","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":[0.003724608,0.001318836,0.001368031,0.003565013,0.0006868346,0.003021945,0.002254791,0.003681588,0.01215228],"category_scores_gemma":[0.007899249,0.0005899323,0.001169308,0.003586599,0.001493266,0.005767351,0.003105865,0.009409695,0.009087004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001090441,"about_ca_system_score_gemma":0.003355323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001154727,"about_ca_topic_score_gemma":0.002204608,"domain_scores_codex":[0.9986218,0.000506408,0.000225583,0.0001609011,0.0003853407,0.00009994924],"domain_scores_gemma":[0.9900879,0.007230179,0.000449586,0.0002883688,0.001319709,0.0006243196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008014095,0.00007352386,0.0002008018,0.007468786,0.000080736,0.0002405385,0.0002135765,0.0003571355,0.001803829,0.01714146,0.2987188,0.6736206],"study_design_scores_gemma":[0.00001014699,0.00001789224,0.000139493,0.002523098,0.00002468619,0.0003553057,0.00003345469,0.00006626589,0.0002613245,0.007088249,0.9894668,0.00001311285],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001429325,0.9331581,0.02235851,0.02635115,0.009950909,0.00008839647,0.0004215109,0.0006232641,0.006905179],"genre_scores_gemma":[0.001940238,0.8925272,0.04878629,0.03687591,0.008120417,0.0002586951,0.001091314,0.0002850886,0.01011489],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01215228,"threshold_uncertainty_score":0.04065347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0641081893372974,"score_gpt":0.3960042864222798,"score_spread":0.3318960970849824,"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."}}