{"id":"W3159344430","doi":"10.1093/bioinformatics/btab249","title":"MetaFusion: a high-confidence metacaller for filtering and prioritizing RNA-seq gene fusion candidates","year":2021,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Computer science; Benchmarking; Data mining; Graph; Fusion; Cluster analysis; Precision and recall; Majority rule; Selection (genetic algorithm); Machine learning; Information retrieval; Artificial intelligence; Theoretical computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001311816,0.0001170319,0.0001307465,0.00003358715,0.0001290856,0.00006894339,0.00008968128,0.0001001882,0.00002140906],"category_scores_gemma":[0.00009311998,0.0001046907,0.00005337395,0.000072064,0.00002901006,0.0000130136,0.0001414727,0.00004341852,0.000003848951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001018255,"about_ca_system_score_gemma":0.00008874357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000610202,"about_ca_topic_score_gemma":0.00001052655,"domain_scores_codex":[0.9992782,0.00001685748,0.0002533766,0.0001787272,0.0001102649,0.000162548],"domain_scores_gemma":[0.9994135,0.0000142062,0.0001018374,0.0002627155,0.0001282662,0.00007941799],"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":[0.00002593121,0.00001072656,0.00003135544,0.00007440453,0.00002531858,9.110423e-7,0.000118259,0.00001128423,0.9872041,0.0003154737,0.001634521,0.01054772],"study_design_scores_gemma":[0.0005735839,0.00007307348,0.0005529098,0.00003800488,0.00003422578,0.00003205568,0.0002725054,0.003015995,0.9265023,0.0001800591,0.06853516,0.0001900755],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7094929,0.004389092,0.2823189,0.0009214186,0.0006742795,0.0005372614,0.00009157668,0.00004390648,0.001530614],"genre_scores_gemma":[0.8529475,0.002736675,0.141106,0.000811459,0.0002122937,0.00008316254,0.0004266145,0.00002400043,0.001652325],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1434546,"threshold_uncertainty_score":0.4269162,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01830368811237904,"score_gpt":0.2595859352805155,"score_spread":0.2412822471681365,"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."}}