{"id":"W2171380954","doi":"10.1503/cmaj.140697","title":"Societal preferences for the return of incidental findings from clinical genomic sequencing: a discrete-choice experiment","year":2015,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Centre for Applied Research in Cancer Control; Cancer Care Ontario; University of British Columbia; BC Cancer Agency","funders":"National Human Genome Research Institute","keywords":"Computer science; Genomic sequencing; Data science; Computational biology; Bioinformatics; Genetics; Biology; Genome","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00110996,0.00008516006,0.0001428544,0.00002004105,0.0001391352,0.00004807934,0.0002982665,0.0002543916,0.0001310603],"category_scores_gemma":[0.001972282,0.00006130891,0.0001865701,0.00003071611,0.00007040355,0.000005235983,0.00004058387,0.0002177916,0.000003952465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002749681,"about_ca_system_score_gemma":0.003445411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002239897,"about_ca_topic_score_gemma":0.008709299,"domain_scores_codex":[0.9987483,0.00009894439,0.0003811441,0.0001491789,0.0003955943,0.0002268141],"domain_scores_gemma":[0.9985623,0.0001478578,0.0002062237,0.0001001923,0.0002279034,0.0007554936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001529468,0.00008932652,0.71798,0.000009329686,0.001192699,0.00003809975,0.001788201,0.00003848731,0.01376474,0.00007357518,0.2581985,0.006674109],"study_design_scores_gemma":[0.007798483,0.001426264,0.4469298,0.0001087605,0.0004033803,0.0001897077,0.01997876,0.001725774,0.007810967,0.001946834,0.5107915,0.0008897973],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959249,0.001273498,0.000144857,0.001591782,0.0006440542,0.0001172553,0.0001625654,0.000001689412,0.0001393859],"genre_scores_gemma":[0.9964506,0.0001583847,0.000149362,0.001444899,0.001595694,0.000009068718,0.00007753952,0.000009594927,0.0001048757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2710502,"threshold_uncertainty_score":0.6112011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03417820693887047,"score_gpt":0.3098375996974247,"score_spread":0.2756593927585543,"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."}}