{"id":"W2613391252","doi":"10.1038/ejhg.2017.64","title":"Practices and views of neurologists regarding the use of whole-genome sequencing in clinical settings: a web-based survey","year":2017,"lang":"en","type":"article","venue":"European Journal of Human Genetics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Université de Montréal; Génome Québec; Genome Canada","keywords":"Neurology; Anticipation (artificial intelligence); Relevance (law); Medicine; Psychology; Psychiatry; Computer science; Political 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":[0.00317942,0.0001150367,0.0002561984,0.00005275836,0.000120573,0.00007830509,0.0004991131,0.00003893358,0.000001687366],"category_scores_gemma":[0.001949877,0.00008326217,0.0001285485,0.00002532497,0.0003163117,0.000009175326,0.000210131,0.0001869793,3.796274e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006148098,"about_ca_system_score_gemma":0.0001509132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001227998,"about_ca_topic_score_gemma":0.00008308591,"domain_scores_codex":[0.997604,0.001149212,0.0008191747,0.0001730361,0.0001230603,0.0001315451],"domain_scores_gemma":[0.9963632,0.0001137355,0.002719465,0.0005003339,0.0002318818,0.00007134194],"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":[0.0003086488,0.0001023541,0.3382037,0.00006896528,0.0001005166,0.0001713497,0.000142334,0.002077575,0.6566843,0.000002969062,0.000436875,0.001700397],"study_design_scores_gemma":[0.001204757,0.001184782,0.9781998,0.00007449942,0.00006479203,0.00005190451,0.00005454682,0.0001862495,0.004042889,0.00000626797,0.01480348,0.0001260379],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980436,0.001491759,0.00004399595,0.0001138677,0.00009106876,0.00008333088,0.0000389273,8.17961e-7,0.00009264179],"genre_scores_gemma":[0.9982247,0.0007078847,0.0007056314,0.0001709794,0.0001392015,2.255427e-7,0.0000102611,0.0000213627,0.00001972349],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6526414,"threshold_uncertainty_score":0.3395333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1817877075032748,"score_gpt":0.3636406146368674,"score_spread":0.1818529071335925,"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."}}