{"id":"W4381612060","doi":"10.1089/crispr.2023.0007","title":"Rapid and Technically Simple Detection of SARS-CoV-2 Variants Using CRISPR Cas12 and Cas13","year":2023,"lang":"en","type":"article","venue":"The CRISPR Journal","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut universitaire de cardiologie et de pneumologie de Québec; Centre National en Électrochimie et en Technologies Environnementales; Collège Shawinigan; Centre hospitalier de l'Université Laval; Université Laval; Héma-Québec; Centre hospitalier universitaire de Québec","funders":"Canadian Institutes of Health Research","keywords":"CRISPR; Loop-mediated isothermal amplification; Sanger sequencing; Amplicon; Computational biology; Pipeline (software); Computer science; Palindrome; Nanopore sequencing; Biology; Virology; Mutation; Genetics; Polymerase chain reaction; Genome; Gene; Operating system","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":[0.0009938575,0.0007060237,0.0006643178,0.0006280285,0.0004403199,0.001126959,0.0006583877,0.0008281766,0.002880272],"category_scores_gemma":[0.001370597,0.0004465439,0.0007655527,0.000272801,0.0004888149,0.0005636235,0.0008946318,0.001218468,0.001827595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004398064,"about_ca_system_score_gemma":0.0007127961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001362149,"about_ca_topic_score_gemma":0.00400852,"domain_scores_codex":[0.9981609,0.0001917839,0.000149466,0.0005092943,0.0008310842,0.0001575854],"domain_scores_gemma":[0.999095,0.0002339452,0.0002077629,0.00018872,0.0001769475,0.00009771987],"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":[0.00007496273,0.00004451886,0.0007873269,0.00006100806,0.00001446427,0.00008473823,0.00003364468,0.0002525436,0.9885556,0.0002391062,0.0003512523,0.00950085],"study_design_scores_gemma":[0.00001049708,0.0001687859,0.002499856,0.00001165415,0.0000170328,0.0004119283,0.00003899739,0.002966325,0.9864718,0.0001373664,0.007221057,0.0000446601],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5026585,0.001692724,0.4735335,0.001073421,0.0003964813,0.0009918889,0.00365438,0.006385227,0.009613846],"genre_scores_gemma":[0.5190294,0.0009608455,0.4639589,0.000471451,0.00003934516,0.0003849152,0.004008549,0.0005804022,0.01056622],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002880272,"threshold_uncertainty_score":0.009635508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03159809360156925,"score_gpt":0.3459736276800011,"score_spread":0.3143755340784318,"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."}}