{"id":"W3217768155","doi":"10.1101/2021.11.28.470285","title":"Targeted profiling of human extrachromosomal DNA by CRISPR-CATCH","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; Cancer Research UK; National Institutes of Health; Jonsson Comprehensive Cancer Center; Deutsche Forschungsgemeinschaft; European Commission; Canadian Institutes of Health Research; Melanoma Research Alliance","keywords":"CRISPR; Extrachromosomal DNA; Biology; DNA; Genetics; Computational biology; Gene; Plasmid","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":[0.0002737561,0.000267058,0.0002834431,0.0003100117,0.0001534176,0.0004671291,0.0002765449,0.00047303,0.001324673],"category_scores_gemma":[0.0003755855,0.000218638,0.0002414199,0.0001889615,0.0002440885,0.0001990007,0.0005191967,0.0006454684,0.0009127982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003591627,"about_ca_system_score_gemma":0.0002216709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007515312,"about_ca_topic_score_gemma":0.001266694,"domain_scores_codex":[0.9996986,0.00002516315,0.00001593927,0.0001049479,0.0001191427,0.00003616875],"domain_scores_gemma":[0.9997268,0.00008441752,0.00006156159,0.00004987826,0.00004272865,0.00003450596],"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":[0.0000182038,0.000004995078,0.0002010937,0.00002837022,0.000006939993,0.00002562532,0.00001437177,0.0001957715,0.9974973,0.0001147649,0.00008553544,0.001807181],"study_design_scores_gemma":[0.000002427789,0.00002599961,0.0009343548,0.000002498047,0.00000499726,0.00008868876,0.000008568776,0.00105335,0.9953193,0.00005505845,0.00250058,0.000004209471],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7820271,0.001638994,0.2048513,0.0003826931,0.0001048063,0.0001432492,0.003780532,0.002484721,0.004586531],"genre_scores_gemma":[0.8899269,0.001048371,0.09465083,0.0002446966,0.00001890215,0.0001382991,0.004048846,0.0005845782,0.009338666],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001324673,"threshold_uncertainty_score":0.004431486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009552869997537815,"score_gpt":0.2308583468956191,"score_spread":0.2213054768980813,"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."}}