{"id":"W2091230935","doi":"10.1002/humu.22008","title":"HGV2011: Personalized genomic medicine meets the incidentalome","year":2011,"lang":"en","type":"article","venue":"Human Mutation","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"National Cancer Institute; National Human Genome Research Institute; University of Toronto; University of Leicester; DNA Genotek","keywords":"Hum; Biology; Human genome; Human genetic variation; Personal genomics; Genome-wide association study; Personalized medicine; Variation (astronomy); Computational biology; Precision medicine; Genome; Data science; Whole genome sequencing; Genomics; Genetics; Single-nucleotide polymorphism; Gene; Computer science","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":[0.0001527269,0.00008588708,0.00006892816,0.00002634907,0.0001973726,0.00001077109,0.0001362324,0.00004822557,0.000629445],"category_scores_gemma":[0.00001345211,0.00006182515,0.00004024323,0.00003137417,0.0001281451,0.000004327071,0.00004085131,0.00003819201,0.000045166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001605821,"about_ca_system_score_gemma":0.00002048501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000212393,"about_ca_topic_score_gemma":0.0001003645,"domain_scores_codex":[0.9994547,0.00005099978,0.0001571067,0.0001462779,0.00007953889,0.0001114215],"domain_scores_gemma":[0.9996634,0.000004499108,0.00007964623,0.0001758251,0.00004750201,0.00002918246],"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":[0.00008759712,0.00008062399,0.007438625,0.00002633177,0.0001546144,0.00001090032,0.01762051,0.00001978798,0.9300102,0.03992394,0.003688434,0.0009384515],"study_design_scores_gemma":[0.003658035,0.001282872,0.8040214,0.00003827269,0.0002271367,0.0003070025,0.01204532,0.00007216048,0.1133794,0.01499785,0.0492205,0.0007500955],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991297,0.0003429263,0.0002997265,0.0001409687,0.00009775411,0.0001216353,0.00000535641,0.00001088431,0.007683715],"genre_scores_gemma":[0.997058,0.0000220442,0.0001645877,0.0002565842,0.0002392259,0.00002461749,0.0001819149,0.00001213426,0.00204087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8166308,"threshold_uncertainty_score":0.6891981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03241842088261827,"score_gpt":0.2517322535957651,"score_spread":0.2193138327131468,"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."}}