{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000475661,0.0001111848,0.000128129,0.00006708899,0.0001718234,0.00003665767,0.0001036294,0.0000909701,0.000003234731],"category_scores_gemma":[0.000098329,0.00008562211,0.00004834549,0.0001227699,0.00007727426,0.000005346268,0.0001178704,0.0001618145,9.277962e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007145938,"about_ca_system_score_gemma":0.0000259782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000325326,"about_ca_topic_score_gemma":0.00002294223,"domain_scores_codex":[0.9992788,0.0000500537,0.000217575,0.0001473743,0.0001029524,0.0002032779],"domain_scores_gemma":[0.9996126,0.00002223181,0.00007855374,0.0001751829,0.00006227689,0.00004911529],"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":[0.00003098798,0.000006350026,0.0001555755,0.00001579242,0.00003581382,0.000007818263,0.00008001326,0.0001370808,0.9914436,0.000004933171,0.0003332896,0.007748793],"study_design_scores_gemma":[0.0003902306,0.0001779824,0.005525112,0.00001739383,0.00005393627,0.001184895,0.0002033943,0.002737815,0.9856579,0.0002501329,0.003673406,0.0001277779],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643446,0.001872815,0.03338736,0.0001166612,0.0001305274,0.00008203743,0.000006441488,0.00001179697,0.00004781656],"genre_scores_gemma":[0.9978142,0.001485506,0.0004102171,0.00006095125,0.0001909308,0.000001747978,0.000002059069,0.0000188354,0.00001549593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03346971,"threshold_uncertainty_score":0.3491568,"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."}}