{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005238221,0.0002940566,0.0003335843,0.001202995,0.000189776,0.000552565,0.0002060779,0.0003219281,0.0007650134],"category_scores_gemma":[0.001006796,0.0001715658,0.0003284728,0.0007814144,0.0002009011,0.000211198,0.0003629112,0.0002857459,0.0002280861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003861707,"about_ca_system_score_gemma":0.000235374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001274643,"about_ca_topic_score_gemma":0.002553623,"domain_scores_codex":[0.9996761,0.00004590926,0.00002524527,0.0001135456,0.00009993975,0.00003923106],"domain_scores_gemma":[0.999691,0.00009168833,0.00007404025,0.00003425966,0.00007431906,0.00003475526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006104913,0.0000623743,0.3998705,0.0002860015,0.0002260908,0.0006431779,0.0001735508,0.003731468,0.5533736,0.0002894517,0.0009759978,0.03975733],"study_design_scores_gemma":[0.00004849363,0.0004643189,0.7712855,0.00007902116,0.0004989578,0.004084275,0.0004802592,0.03417227,0.1813412,0.001047592,0.006454971,0.00004327125],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856564,0.001449404,0.008493485,0.0001240175,0.00001263725,0.00005034623,0.003078176,0.0001866479,0.0009487582],"genre_scores_gemma":[0.9875721,0.0004100522,0.008285653,0.0001180492,0.00001422488,0.00003736664,0.003213055,0.00003056672,0.0003189557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001274643,"threshold_uncertainty_score":0.002801836,"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."}}