{"id":"W3113877554","doi":"10.1021/acssensors.0c02175","title":"Microfluidic Technology for Antibacterial Resistance Study and Antibiotic Susceptibility Testing: Review and Perspective","year":2020,"lang":"en","type":"review","venue":"ACS Sensors","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Microfluidics; Antibiotic resistance; Antibiotics; Nanotechnology; Risk analysis (engineering); Medicine; Intensive care medicine; Computer science; Biology; Microbiology; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004977891,0.000459902,0.001412614,0.00007215761,0.0001807247,0.00008293417,0.0002541897,0.0003706946,0.000003802804],"category_scores_gemma":[0.004091416,0.0004298617,0.0001354826,0.0003641716,0.0002623373,0.000006122962,0.0002729328,0.0002273488,0.000004803892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004807284,"about_ca_system_score_gemma":0.0001815956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001270787,"about_ca_topic_score_gemma":0.00002845249,"domain_scores_codex":[0.9973087,0.0002896608,0.0006750058,0.001352117,0.0000823279,0.0002921579],"domain_scores_gemma":[0.9983318,0.0001244531,0.0003968595,0.0006746124,0.0003588175,0.0001133895],"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":[0.0003025746,0.001302568,0.004459964,0.2214025,0.002102846,0.0000651715,0.0007611332,1.702442e-8,0.1780043,0.0002904429,0.01349112,0.5778173],"study_design_scores_gemma":[0.0005541889,0.0006521256,0.0003245909,0.00476916,0.001914591,0.00008653788,0.0004385637,2.588651e-7,0.0004859779,0.00005130212,0.9899671,0.0007555767],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02808128,0.9681397,0.00000411977,0.0003002496,0.0001348217,0.003116261,0.0001280899,0.00005575873,0.00003969622],"genre_scores_gemma":[0.004298038,0.9945002,0.0004408139,0.00006730093,0.0002164759,0.00004665105,0.0001331476,0.00006422885,0.0002331986],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.976476,"threshold_uncertainty_score":0.9998153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04581863075430684,"score_gpt":0.3372082537831843,"score_spread":0.2913896230288774,"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."}}