{"id":"W3123897428","doi":"10.1093/bib/bbaa403","title":"Oxford nanopore sequencing in clinical microbiology and infection diagnostics","year":2020,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Workflow; Nanopore sequencing; Turnaround time; Context (archaeology); Point of care; Computer science; Identification (biology); Clinical microbiology; Point-of-care testing; Software; Molecular diagnostics; Data science; DNA sequencing; Medicine; Bioinformatics; Biology; Microbiology; Database; Pathology","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":[0.007565993,0.0008790968,0.001231679,0.002159796,0.0005473549,0.003103817,0.00126606,0.003532182,0.005624395],"category_scores_gemma":[0.008291771,0.0007782376,0.000747884,0.001821705,0.001530755,0.003171094,0.002277243,0.003652219,0.003765156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001655829,"about_ca_system_score_gemma":0.002169857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002074258,"about_ca_topic_score_gemma":0.003035364,"domain_scores_codex":[0.994152,0.002392657,0.0006107466,0.0007952285,0.001689606,0.0003597302],"domain_scores_gemma":[0.9915146,0.004450216,0.0006894607,0.0005225783,0.002118144,0.0007050224],"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":[0.0003905665,0.00006745238,0.004381024,0.007960819,0.0001845497,0.000547347,0.0004517864,0.00163682,0.02161553,0.03266463,0.1415049,0.7885945],"study_design_scores_gemma":[0.00002366945,0.000177975,0.003023099,0.002742512,0.00007503565,0.001376726,0.000169295,0.001411233,0.00995933,0.01371622,0.9672166,0.0001084469],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005057794,0.8658822,0.05682476,0.0329832,0.0156018,0.0001561455,0.001253959,0.001101129,0.02113891],"genre_scores_gemma":[0.05220338,0.7630687,0.123724,0.02499457,0.01316495,0.0004117649,0.002565606,0.0003576118,0.01950947],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007565993,"threshold_uncertainty_score":0.04001325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387400978782597,"score_gpt":0.2822925424533028,"score_spread":0.2484185326654769,"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."}}