{"id":"W4366774211","doi":"10.1021/acsmeasuresciau.3c00005","title":"Multiplex Assays Enable Simultaneous Detection and Identification of SARS-CoV-2 Variants of Concern in Clinical and Wastewater Samples","year":2023,"lang":"en","type":"article","venue":"ACS Measurement Science Au","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Provincial Laboratory of Public Health; University of Alberta Hospital; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates; Canada Research Chairs; Alberta Health; Social Sciences and Humanities Research Council of Canada; University of Alberta; Faculty of Medicine and Dentistry, University of Alberta; Alberta Precision Laboratories","keywords":"Multiplex; Biology; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Coronavirus disease 2019 (COVID-19); Virology; Computational biology; Molecular biology; Medicine; Genetics; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001845962,0.001342729,0.0007809537,0.001600457,0.0003160432,0.001227012,0.0004531254,0.000814834,0.001223956],"category_scores_gemma":[0.001901873,0.0006756198,0.0004133677,0.0006276186,0.0003405574,0.0006656979,0.0007364044,0.0008138857,0.0007082873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000447966,"about_ca_system_score_gemma":0.0003352092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004692005,"about_ca_topic_score_gemma":0.001201452,"domain_scores_codex":[0.9977136,0.000524129,0.0001896828,0.0005264735,0.0008626444,0.0001835277],"domain_scores_gemma":[0.9986972,0.000367278,0.0004047856,0.0001213375,0.0002927053,0.0001166747],"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":[0.0007054211,0.0002229952,0.01781172,0.000225986,0.00009478578,0.0001966307,0.0001818625,0.0009630095,0.919338,0.0004443713,0.0007714747,0.05904371],"study_design_scores_gemma":[0.00003835983,0.001332345,0.01894909,0.00006688707,0.000116822,0.001383106,0.0001530792,0.01299815,0.9556685,0.0007827348,0.008436487,0.00007445081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7209753,0.008515913,0.2526805,0.000811888,0.0004596631,0.001071078,0.004464203,0.003192445,0.007829019],"genre_scores_gemma":[0.7767242,0.002934258,0.2117432,0.0003914342,0.0001669448,0.0005649265,0.001832638,0.00006215357,0.005580303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001845962,"threshold_uncertainty_score":0.009762466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2185537909403604,"score_gpt":0.3782522210200178,"score_spread":0.1596984300796574,"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."}}