{"id":"W3083792114","doi":"10.1186/s12885-020-07304-3","title":"Bayesian copy number detection and association in large-scale studies","year":2020,"lang":"en","type":"article","venue":"BMC Cancer","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"National Cancer Institute; National Institutes of Health; National Center for Advancing Translational Sciences; World Health Organization","keywords":"Copy-number variation; Bayesian probability; Genome-wide association study; Computational biology; Computer science; Biology; Genetics; Genome; Single-nucleotide polymorphism; Artificial intelligence; Gene","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":[0.00006458372,0.00005401405,0.000073283,0.000006796892,0.00004025453,0.00001064468,0.00002422117,0.00005851319,0.00003902574],"category_scores_gemma":[0.0000341413,0.00005415793,0.00001979822,0.00004499128,0.000008250028,0.000003354702,0.00003473136,0.00003505636,0.000004522038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004314353,"about_ca_system_score_gemma":0.00002826127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005534838,"about_ca_topic_score_gemma":0.002977006,"domain_scores_codex":[0.9996045,0.00002568257,0.0000901637,0.0001345244,0.00004427502,0.0001008026],"domain_scores_gemma":[0.9998507,0.000005854077,0.00004095408,0.00004271359,0.00003379331,0.00002602168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000443223,0.00001391949,0.971018,0.0000415078,0.00003961757,3.268367e-7,0.001180483,0.0001430807,0.02616194,0.00002340794,0.0009072664,0.000426141],"study_design_scores_gemma":[0.004059361,0.000307262,0.543172,0.00005495986,0.0001043652,0.000008625918,0.009843592,0.002809662,0.3080225,0.0003750028,0.1304636,0.0007790659],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968532,0.0008923831,0.001325734,0.0003585468,0.00009639031,0.00007049121,0.0000259309,0.000006387438,0.0003709495],"genre_scores_gemma":[0.9981459,0.0004794206,0.0002281038,0.0003442898,0.000223442,0.00003584438,0.000008254498,0.000006113634,0.0005286278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.427846,"threshold_uncertainty_score":0.2208496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393800392525358,"score_gpt":0.2687776987103504,"score_spread":0.2548396947850968,"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."}}