{"id":"W2300793657","doi":"10.1016/j.mimet.2016.02.016","title":"Next-generation sequencing (NGS) in the microbiological world: How to make the most of your money","year":2016,"lang":"en","type":"review","venue":"Journal of Microbiological Methods","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":165,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Institut Universitaire de Cardiologie et de Pneumologie de Québec","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Australian Institute of Criminology","keywords":"DNA sequencing; Sanger sequencing; Computational biology; Genome; Data science; Biology; Computer science; DNA; Genetics; 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":[0.00421722,0.001516772,0.002601701,0.002384573,0.0005555729,0.002894833,0.002682479,0.004510788,0.005866654],"category_scores_gemma":[0.005077088,0.0005250368,0.0009465047,0.002749879,0.001793794,0.005630479,0.001857371,0.006060775,0.005502394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001464298,"about_ca_system_score_gemma":0.003002842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002064981,"about_ca_topic_score_gemma":0.002796382,"domain_scores_codex":[0.9983387,0.0002612462,0.0001440954,0.0002106719,0.0009302508,0.0001150769],"domain_scores_gemma":[0.995037,0.002358014,0.0003898339,0.0001534953,0.001508992,0.000552711],"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":[0.00006789622,0.0000366833,0.0001424475,0.006130741,0.00005506039,0.00009492628,0.00003485166,0.0002413102,0.002130232,0.003706326,0.08492644,0.902433],"study_design_scores_gemma":[0.00001049957,0.00004268582,0.0003109975,0.002519847,0.00006199122,0.0004474927,0.00007176947,0.0002108077,0.001024739,0.004609801,0.9906465,0.0000429072],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008209645,0.9902063,0.001492419,0.004379402,0.002665166,0.000009004633,0.00003973197,0.00004553665,0.001080335],"genre_scores_gemma":[0.0005459581,0.9917571,0.002542831,0.002055888,0.001590965,0.0000124429,0.00008211171,0.00001624426,0.001396472],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005866654,"threshold_uncertainty_score":0.02230304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2046075617072343,"score_gpt":0.4004160120235812,"score_spread":0.1958084503163468,"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."}}