{"id":"W2099377894","doi":"10.1093/bioinformatics/bts053","title":"JointSNVMix: a probabilistic model for accurate detection of somatic mutations in normal/tumour paired next-generation sequencing data","year":2012,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":175,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia; BC Cancer Agency","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Somatic cell; DNA sequencing; Computational biology; Probabilistic logic; Computer science; Genetics; Biology; Artificial intelligence; Gene","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":[0.0003755318,0.0001203821,0.0001422883,0.00007085869,0.0000621322,0.0000320816,0.0001747,0.00009625095,0.000001711562],"category_scores_gemma":[0.0005317164,0.0001220425,0.00004322989,0.00008348932,0.00003297113,0.00006130994,0.0001095745,0.00004546596,0.000003141185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006641131,"about_ca_system_score_gemma":0.0002183612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002738092,"about_ca_topic_score_gemma":0.0004147325,"domain_scores_codex":[0.9990316,0.00001626697,0.0005097901,0.0001167875,0.00009093881,0.0002346273],"domain_scores_gemma":[0.9991806,0.00003828634,0.0002328065,0.0004029541,0.00008267429,0.00006264492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005807868,0.0001351031,0.0004759067,0.0006013881,0.00004601016,1.680462e-7,0.002511745,0.09065896,0.8965666,0.0002451264,0.000608123,0.00809283],"study_design_scores_gemma":[0.0004254118,0.0000711639,0.0001503504,0.00001977302,0.00003656932,0.000005268166,0.0002941058,0.9327474,0.0657937,0.0001584025,0.0001561729,0.0001416507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6265405,0.0001753844,0.3721442,0.00003373011,0.0001687661,0.0005729353,0.0002816398,0.000008973617,0.00007381314],"genre_scores_gemma":[0.9640478,0.00006344961,0.03443436,0.00006970437,0.0001455067,0.00006723549,0.001134487,0.00001524634,0.00002224228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8420885,"threshold_uncertainty_score":0.4976747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1153016910058751,"score_gpt":0.2866914171935863,"score_spread":0.1713897261877111,"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."}}