{"id":"W4385638678","doi":"10.1038/s41551-023-01078-2","title":"Sensing the DNA-mismatch tolerance of catalytically inactive Cas9 via barcoded DNA nanostructures in solid-state nanopores","year":2023,"lang":"en","type":"article","venue":"Nature Biomedical Engineering","topic":"Nanopore and Nanochannel Transport Studies","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Engineering and Physical Sciences Research Council; Cambridge Trust; University of Cambridge; European Commission; Research Councils UK; Oxford Nanopore Technologies","keywords":"DNA; Nanopore; Cas9; DNA sequencing; Biology; Nanopore sequencing; Ribonucleoprotein; Computational biology; Nucleic acid; Biophysics; CRISPR; Cell biology; Nanotechnology; Biochemistry; RNA; Materials science; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002566519,0.0002622033,0.0002761332,0.0001359184,0.0001772428,0.0003593408,0.0005158281,0.0005136624,0.0003515624],"category_scores_gemma":[0.0006835681,0.0002303692,0.0001943425,0.0001152554,0.0004665004,0.0004847291,0.0002577507,0.000439115,0.0002132904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005081567,"about_ca_system_score_gemma":0.0002258145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009235439,"about_ca_topic_score_gemma":0.001785866,"domain_scores_codex":[0.9997343,0.00003324469,0.0000195927,0.00008600873,0.0001034377,0.0000233471],"domain_scores_gemma":[0.9995223,0.000199411,0.0001241457,0.00003673822,0.00007987511,0.00003759599],"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":[0.00001562715,0.000006247667,0.00007402612,0.00001583186,0.000001966362,0.00001109511,0.000009960244,0.0001954341,0.9992524,0.00007047493,0.000007180337,0.0003397188],"study_design_scores_gemma":[0.000001661646,0.00002285957,0.0002066253,0.000001189059,0.000002196351,0.00001731196,0.000005931784,0.002221395,0.9973241,0.0000259496,0.0001668124,0.000003994526],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9663841,0.000369959,0.03182311,0.000101857,0.00004108279,0.00003847321,0.000239116,0.0002135998,0.000788694],"genre_scores_gemma":[0.9638159,0.00020542,0.03455836,0.00006034477,0.000007544596,0.00004822635,0.0001832334,0.00002695151,0.00109406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009235439,"threshold_uncertainty_score":0.003686965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003595586087765367,"score_gpt":0.2142533245644038,"score_spread":0.2106577384766384,"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."}}