{"id":"W4282922862","doi":"10.1039/d2lc00242f","title":"Automated sample-to-answer centrifugal microfluidic system for rapid molecular diagnostics of SARS-CoV-2","year":2022,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada","keywords":"Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); Point-of-care testing; Loop-mediated isothermal amplification; Computer science; Sample (material); Computational biology; Reliability engineering; Medicine; Engineering; Biology; Chemistry; Chromatography; Immunology; Infectious disease (medical specialty)","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":[],"consensus_categories":[],"category_scores_codex":[0.00009333318,0.0001224033,0.0001952755,0.0001096148,0.00005971552,0.0000137755,0.0001078791,0.00005113329,0.00001464082],"category_scores_gemma":[0.00009560593,0.0001255362,0.0001012304,0.0002701399,0.00001037977,0.00001265595,0.00002886492,0.0001161757,0.00001128572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009945171,"about_ca_system_score_gemma":0.00001443892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001601288,"about_ca_topic_score_gemma":0.000001132451,"domain_scores_codex":[0.9992325,0.00003255854,0.00021317,0.0001533365,0.0001557114,0.0002126915],"domain_scores_gemma":[0.999583,0.0001345491,0.00002628232,0.000175163,0.0000332304,0.00004778678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006362096,0.00008878022,0.00002868675,0.000347192,0.00007588621,0.00001139055,0.00006673448,0.002714486,0.9777352,0.00408195,0.01238724,0.002398857],"study_design_scores_gemma":[0.0004527373,0.0002145942,0.0001132949,0.00006182255,0.00004365225,0.000006762265,0.00004901544,0.04521625,0.9068549,0.00006671048,0.04673566,0.0001846426],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977376,0.001127922,0.01705149,0.00009697262,0.001267016,0.0006325552,0.0007017896,0.001047187,0.0006990701],"genre_scores_gemma":[0.9989939,0.00002603356,0.0005807256,0.0002203031,0.00004960586,0.00005421836,0.00002722654,0.00003837797,0.000009560514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07088032,"threshold_uncertainty_score":0.5119218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01489722558456378,"score_gpt":0.2370774461204621,"score_spread":0.2221802205358983,"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."}}