{"id":"W4283316992","doi":"10.1002/admt.202200208","title":"Innovations and Challenges in Electroanalytical Tools for Rapid Biosurveillance of SARS‐CoV‐2","year":2022,"lang":"en","type":"article","venue":"Advanced Materials Technologies","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"New Brunswick Innovation Foundation; Fondation de la recherche en santé du Nouveau-Brunswick","keywords":"Point-of-care testing; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Internet of Things; Computer science; Coronavirus; Point of care; Nanotechnology; Infectious disease (medical specialty); Virology; Medicine; Disease; Internet privacy; Immunology; Pathology","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":[0.009654082,0.00110531,0.0007399177,0.002007886,0.0006836075,0.00354744,0.00178538,0.002796063,0.002370087],"category_scores_gemma":[0.005395273,0.0005769067,0.0008935567,0.001159722,0.002083682,0.005423526,0.001922388,0.003045858,0.001724142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009238388,"about_ca_system_score_gemma":0.001671643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000684306,"about_ca_topic_score_gemma":0.0009304273,"domain_scores_codex":[0.9949581,0.001651263,0.0002753013,0.0007263561,0.002093901,0.0002951254],"domain_scores_gemma":[0.9948559,0.002328341,0.0003564476,0.0003921155,0.001861566,0.0002054941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002620445,0.0002507447,0.005591722,0.005864427,0.000131497,0.0009841904,0.001109299,0.004027999,0.1486605,0.1025933,0.01748454,0.7130398],"study_design_scores_gemma":[0.00004167869,0.001003078,0.004776946,0.002811073,0.0001842886,0.004727012,0.002377853,0.02627819,0.1341425,0.08246832,0.7408755,0.0003134508],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03809055,0.594253,0.2713847,0.04903268,0.00463782,0.0003153123,0.0004029663,0.0009079315,0.040975],"genre_scores_gemma":[0.2669002,0.4068204,0.2937366,0.01234206,0.004830457,0.0004718852,0.0005079213,0.0002346417,0.01415578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009654082,"threshold_uncertainty_score":0.05105633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1174484206013543,"score_gpt":0.3377194678366288,"score_spread":0.2202710472352745,"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."}}