{"id":"W4306412179","doi":"10.1038/s41588-022-01190-0","title":"Targeted profiling of human extrachromosomal DNA by CRISPR-CATCH","year":2022,"lang":"en","type":"article","venue":"Nature Genetics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft; Rosetrees Trust; European Commission; National Human Genome Research Institute; Wellcome Trust; Francis Crick Institute; National Institutes of Health; Cancer Research UK; Jonsson Comprehensive Cancer Center; Canadian Institutes of Health Research; National Institute of General Medical Sciences; National Institute for Health and Care Research; National Cancer Institute; Melanoma Research Alliance; National Institute of Allergy and Infectious Diseases; Howard Hughes Medical Institute","keywords":"Biology; CRISPR; Extrachromosomal DNA; Genetics; DNA; Amplicon; Gene; Enhancer; Cas9; Computational biology; Gene expression; Plasmid; Polymerase chain reaction","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000210908,0.0002919273,0.0002457117,0.0003128931,0.0001310142,0.0003591865,0.0002236013,0.000436438,0.0009277725],"category_scores_gemma":[0.0004236999,0.0001966775,0.0002146168,0.0001795078,0.0002165618,0.0001768287,0.0003755687,0.0004914342,0.0005203405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002617492,"about_ca_system_score_gemma":0.0001619167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005877116,"about_ca_topic_score_gemma":0.001561771,"domain_scores_codex":[0.9997306,0.00002272325,0.00001371035,0.0001103906,0.00009121028,0.00003134358],"domain_scores_gemma":[0.9997141,0.00009516257,0.0000706632,0.00003997923,0.00004483559,0.00003529087],"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":[0.00001152802,0.000003162929,0.0001764276,0.00002296561,0.000004818358,0.00001284997,0.00001031732,0.00009143772,0.9984515,0.00003542253,0.00001591361,0.001163689],"study_design_scores_gemma":[0.000001657518,0.0000440867,0.001873045,0.000003009276,0.000007017767,0.00009971562,0.00001052324,0.0008177682,0.9957243,0.00003657587,0.001378443,0.000003847224],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8631402,0.001628772,0.1285717,0.0001806934,0.00004696796,0.0001212306,0.002285087,0.001131069,0.002894291],"genre_scores_gemma":[0.9242054,0.00111206,0.06662246,0.0001584204,0.000008930405,0.0001150394,0.002590668,0.0002544105,0.004932631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009277725,"threshold_uncertainty_score":0.003103733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005729933780264319,"score_gpt":0.2576081929684597,"score_spread":0.2518782591881953,"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."}}