{"id":"W3174027460","doi":"10.1039/d1cc02546e","title":"CRISPR/Cas12a-mediated gold nanoparticle aggregation for colorimetric detection of SARS-CoV-2","year":2021,"lang":"en","type":"article","venue":"Chemical Communications","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Hospital Edmonton; University of Alberta","funders":"Canadian Institutes of Health Research; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Alberta Precision Laboratories","keywords":"CRISPR; Colloidal gold; Nanoparticle; RNA; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Cleavage (geology); Coronavirus disease 2019 (COVID-19); Chemistry; Nanotechnology; 2019-20 coronavirus outbreak; Combinatorial chemistry; Virology; Biology; Materials science; Biochemistry; Infectious disease (medical specialty); Gene; Medicine","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":[0.0004545349,0.0004892484,0.0004933141,0.0003757587,0.000355481,0.0004292962,0.0005603664,0.0006840462,0.001112181],"category_scores_gemma":[0.0003555462,0.000437328,0.000398085,0.0002442144,0.0002628423,0.0002754085,0.0004288829,0.0007177602,0.0007289634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006916954,"about_ca_system_score_gemma":0.0003738229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001287408,"about_ca_topic_score_gemma":0.003088275,"domain_scores_codex":[0.9992737,0.00008860946,0.00005484221,0.0002392695,0.0002463541,0.0000972483],"domain_scores_gemma":[0.9998533,0.0000335745,0.00002505179,0.00002156296,0.00004305781,0.00002358838],"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":[0.00001655576,0.00001074188,0.00002725986,0.00002132966,0.00000239364,0.00001501879,0.00001118036,0.00009153914,0.9985251,0.00007345142,0.00009530718,0.001110132],"study_design_scores_gemma":[0.000003337031,0.00002903993,0.0002146178,0.000001930235,0.00000328997,0.000046824,0.00000430675,0.003037502,0.9958096,0.00002372024,0.0008198643,0.000006010833],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8270066,0.002542323,0.1540998,0.0005746991,0.0002805285,0.0002652566,0.0009189153,0.002618121,0.0116938],"genre_scores_gemma":[0.905018,0.0008344323,0.08309422,0.0002069718,0.00002338686,0.0002145621,0.000659176,0.0001094593,0.009839741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001287408,"threshold_uncertainty_score":0.005018651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03403935691764336,"score_gpt":0.3445082914423324,"score_spread":0.310468934524689,"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."}}