{"id":"W2122231539","doi":"10.1503/cmaj.100300","title":"Navigating the road to personalized medicine: Can we believe?","year":2010,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital","funders":"","keywords":"Personalized medicine; Phrase; Genomic medicine; Computer science; Data science; Precision medicine; Health care; World Wide Web; Alternative medicine; Medicine; Bioinformatics; Artificial intelligence; Computational biology; Pathology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009940946,0.001164982,0.002174398,0.001084539,0.00465257,0.006031435,0.002665859,0.04042191,0.01463377],"category_scores_gemma":[0.04113968,0.0006425673,0.001296139,0.0009448639,0.0094656,0.01600786,0.003422972,0.07327231,0.01000006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005714706,"about_ca_system_score_gemma":0.007001223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007406196,"about_ca_topic_score_gemma":0.01285873,"domain_scores_codex":[0.9935766,0.00247696,0.0004599086,0.0006896613,0.002238267,0.0005586616],"domain_scores_gemma":[0.9686443,0.02023647,0.001059443,0.0008620357,0.004541811,0.004655932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004579911,0.00004018593,0.0002988699,0.00018613,0.00002749775,0.0006779876,0.0002265194,0.00008634915,0.0001070427,0.007780928,0.9679672,0.02255545],"study_design_scores_gemma":[0.0001873498,0.0001276489,0.001012046,0.0012861,0.00006804696,0.003469276,0.001910357,0.0007653207,0.0001966009,0.08107994,0.9097541,0.000143184],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00004140302,0.002573613,0.0001404832,0.9908683,0.005569513,0.000003287664,0.00001051864,0.00001321551,0.0007796287],"genre_scores_gemma":[0.002042,0.00700514,0.0006667511,0.9557108,0.03281116,0.00001605148,0.00002116945,0.0000175734,0.001709496],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.04042191,"threshold_uncertainty_score":0.05257338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005560528653356744,"score_gpt":0.2432199529645706,"score_spread":0.2376594243112139,"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."}}