{"id":"W3092410196","doi":"10.1088/2516-1091/abbf5e","title":"Critical review on where CRISPR meets molecular diagnostics","year":2020,"lang":"en","type":"article","venue":"Progress in Biomedical Engineering","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"CRISPR; Nucleic acid detection; Molecular diagnostics; Computational biology; Computer science; Trans-activating crRNA; Nanotechnology; Genome editing; Nucleic acid; Biology; Bioinformatics; Genetics; Gene; Materials science","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":[0.002560522,0.001226398,0.001437973,0.002261715,0.0005551761,0.002560451,0.002179149,0.00461444,0.01663769],"category_scores_gemma":[0.005114731,0.0004453989,0.0009366683,0.001411597,0.001320922,0.003529536,0.001508778,0.006076157,0.009052248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002138264,"about_ca_system_score_gemma":0.003346407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001264776,"about_ca_topic_score_gemma":0.001671126,"domain_scores_codex":[0.9988752,0.0002721217,0.0001479507,0.0001846309,0.0003938973,0.0001262126],"domain_scores_gemma":[0.995522,0.002077671,0.0003019199,0.0001509737,0.001454314,0.0004930967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008167002,0.00002820694,0.00006871838,0.007913519,0.00005563965,0.000371505,0.00005603274,0.0002267903,0.00145472,0.01532041,0.5715054,0.4029174],"study_design_scores_gemma":[0.000007565184,0.00002786734,0.0000568123,0.001594701,0.00001737801,0.0003432837,0.00001785981,0.00002532264,0.0002213723,0.002326844,0.9953505,0.00001040737],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001040212,0.9298431,0.001438889,0.03437317,0.02741647,0.00003443731,0.0001026598,0.0001385418,0.006548719],"genre_scores_gemma":[0.001394163,0.9515982,0.001281144,0.02578828,0.01340082,0.00005797612,0.0001907718,0.00004307795,0.006245564],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01663769,"threshold_uncertainty_score":0.05565858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009715140046815061,"score_gpt":0.318654054373315,"score_spread":0.3089389143264999,"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."}}