{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007470036,0.00009862046,0.0001420032,0.00004425731,0.00003980257,0.00002309604,0.0000460306,0.0001573554,0.000002605178],"category_scores_gemma":[0.0001862276,0.00008791314,0.00002780022,0.0003954242,0.0001012525,0.0000512643,0.00001522324,0.0001093169,6.629032e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000397675,"about_ca_system_score_gemma":0.000005385774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001346968,"about_ca_topic_score_gemma":0.000004915404,"domain_scores_codex":[0.9993547,0.000007401942,0.0002500407,0.0001865854,0.00007493341,0.0001263379],"domain_scores_gemma":[0.9996994,0.00007215676,0.00004448191,0.00009429114,0.00005562499,0.00003400799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002124582,0.00001927535,0.0002545355,0.0001422553,0.00001686034,1.95655e-7,0.00003580818,0.0002862234,0.996835,0.00008772067,0.000005307765,0.002295582],"study_design_scores_gemma":[0.0001412311,0.00001861547,0.000415101,0.00001004834,0.00002959896,0.000002093378,0.00006942126,0.5106475,0.4884267,0.00007123641,0.0001130773,0.00005529549],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8228382,0.0001728832,0.1763911,0.0003702599,0.0000126583,0.0001268816,0.000006759636,0.00005937466,0.00002187695],"genre_scores_gemma":[0.999714,0.00004994316,0.0001123431,0.00005048266,0.00003745947,0.000009465175,0.000008160827,0.00001541986,0.000002768021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5103613,"threshold_uncertainty_score":0.3584994,"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."}}