{"id":"W3109667847","doi":"10.1021/acs.analchem.0c04047","title":"Isothermal Amplification and Ambient Visualization in a Single Tube for the Detection of SARS-CoV-2 Using Loop-Mediated Amplification and CRISPR Technology","year":2020,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":262,"is_retracted":false,"has_abstract":true,"ca_institutions":"Provincial Laboratory of Public Health; University of Alberta Hospital; University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates; Alberta Health","keywords":"Chemistry; Loop-mediated isothermal amplification; Tube (container); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); CRISPR; Isothermal process; Recombinase Polymerase Amplification; Coronavirus disease 2019 (COVID-19); DNA; Biochemistry; Gene; Thermodynamics; Physics","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":[0.001411116,0.0009102334,0.001061239,0.0008228704,0.0002886813,0.0006664161,0.0009008036,0.0007611397,0.001633641],"category_scores_gemma":[0.001197893,0.0005680692,0.0009051611,0.0003612963,0.0004747414,0.0004623494,0.0008403371,0.001217918,0.001364481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000330733,"about_ca_system_score_gemma":0.0003841485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003587684,"about_ca_topic_score_gemma":0.0006562527,"domain_scores_codex":[0.9981021,0.0004503659,0.0001063203,0.0005695258,0.0006078859,0.0001637194],"domain_scores_gemma":[0.9989755,0.0004134147,0.0002025687,0.0001450124,0.0001867487,0.00007682951],"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":[0.00004853753,0.00003252403,0.0003224153,0.00008707478,0.00001301445,0.00004221356,0.00005002344,0.000178574,0.99445,0.00009638299,0.0001494346,0.004529865],"study_design_scores_gemma":[0.000008900959,0.0002467176,0.001264906,0.00001224621,0.00002622077,0.0003035359,0.00001952984,0.004998212,0.9910445,0.00009759792,0.001950591,0.0000270258],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2415187,0.001607594,0.7469816,0.0002637489,0.0002386814,0.000514438,0.001022938,0.005469512,0.002382825],"genre_scores_gemma":[0.4067089,0.001268526,0.5836951,0.0001990732,0.00009080771,0.001211968,0.001475657,0.0003431606,0.005006895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001633641,"threshold_uncertainty_score":0.00746274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03779079308297809,"score_gpt":0.2727468386670784,"score_spread":0.2349560455841003,"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."}}