{"id":"W3097296206","doi":"10.1158/1078-0432.ccr-20-1900","title":"Uncovering Clinically Relevant Gene Fusions with Integrated Genomic and Transcriptomic Profiling of Metastatic Cancers","year":2020,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia; Pancreas Centre (Canada); Canada's Michael Smith Genome Sciences Centre; BC Cancer Agency","funders":"Canadian Institutes of Health Research; Ipsen; BC Cancer Foundation; Vancouver Coastal Health Research Institute; Eisai; Amgen; Pfizer; Canada Research Chairs; AstraZeneca; Eli Lilly and Company","keywords":"Transcriptome; RNA-Seq; Computational biology; Gene; Fusion gene; Biology; Genome; RNA; Cancer; Contig; Breakpoint; Genetics; Bioinformatics; Gene expression; Chromosomal translocation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001147053,0.000163641,0.0004066963,0.0000461966,0.00009572074,0.00003091798,0.0002956931,0.0001240432,0.00003891217],"category_scores_gemma":[0.0009532802,0.0001350011,0.0001120843,0.0002570083,0.0005583359,0.000004627798,0.000212249,0.000523854,0.000003368563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006716106,"about_ca_system_score_gemma":0.001759483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005157531,"about_ca_topic_score_gemma":0.0005691815,"domain_scores_codex":[0.9977519,0.000226302,0.0007345596,0.0006336519,0.0002712022,0.0003823985],"domain_scores_gemma":[0.9984925,0.0003454752,0.0001418997,0.0003164156,0.0003460843,0.0003576037],"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":[0.005176863,0.0001211527,0.05174514,0.0002239028,0.0003922896,0.00002667019,0.000219307,0.003045512,0.9209645,0.00008287379,0.001460445,0.01654131],"study_design_scores_gemma":[0.02547768,0.03273027,0.07002951,0.0009064168,0.0008975302,0.00004855715,0.003532099,0.01134265,0.7370893,0.001375104,0.1138858,0.002685126],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934561,0.00328417,0.001280478,0.0009869774,0.0001258691,0.0004777374,0.0002357273,0.000008914509,0.0001440454],"genre_scores_gemma":[0.979308,0.01497853,0.004525631,0.0006561178,0.0003193855,0.00007149531,0.00005229714,0.00004367306,0.00004487028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1838753,"threshold_uncertainty_score":0.5505183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.117945335000127,"score_gpt":0.4254958928007959,"score_spread":0.307550557800669,"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."}}