{"id":"W3197021219","doi":"10.1021/acs.analchem.1c03456","title":"Integrating Reverse Transcription Recombinase Polymerase Amplification with CRISPR Technology for the One-Tube Assay of RNA","year":2021,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":129,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Food Inspection Agency; Provincial Laboratory of Public Health; University of Alberta Hospital; University of Alberta","funders":"Li Ka Shing Institute of Virology, University of Alberta; China Scholarship Council; Canadian Institutes of Health Research; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Recombinase Polymerase Amplification; Trans-activating crRNA; RNA; Molecular biology; Chemistry; Reverse transcriptase; Complementary DNA; CRISPR; Amplicon; Nucleic acid; DNA; RNase P; Cas9; Loop-mediated isothermal amplification; Biology; Gene; Polymerase chain reaction; Biochemistry","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":[0.001476675,0.001387996,0.001141823,0.0007195292,0.0003238904,0.001091787,0.001041163,0.001317001,0.001414356],"category_scores_gemma":[0.001660211,0.0008021054,0.001052934,0.0003547399,0.0006575202,0.0006497781,0.0008452801,0.001930485,0.001862416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003972042,"about_ca_system_score_gemma":0.0004012289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003010707,"about_ca_topic_score_gemma":0.0009635519,"domain_scores_codex":[0.9971939,0.0007962869,0.0002654795,0.0006606079,0.0008979251,0.0001857325],"domain_scores_gemma":[0.9981963,0.000790384,0.0004062967,0.0002930676,0.0002149806,0.00009898331],"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":[0.00001648175,0.00002285429,0.0001496757,0.00008464743,0.00001174855,0.00003746026,0.00002200152,0.00009752779,0.9961958,0.0001238536,0.00006295306,0.003174921],"study_design_scores_gemma":[0.00000318686,0.0001113677,0.0003482849,0.000007600768,0.00001762391,0.0001700066,0.000008060546,0.001275552,0.996409,0.00006097899,0.001575318,0.00001305916],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1550142,0.001830835,0.8359218,0.0002778866,0.0002771733,0.0006709428,0.0006447785,0.003405672,0.001956783],"genre_scores_gemma":[0.3172733,0.001666562,0.6722503,0.0002410717,0.00009084326,0.0009353652,0.001841328,0.0004100178,0.005291305],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001476675,"threshold_uncertainty_score":0.00780952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01202129657903517,"score_gpt":0.2872562592167393,"score_spread":0.2752349626377041,"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."}}