{"id":"W2049444570","doi":"10.3747/co.20.1253","title":"Benefits, Issues, and Recommendations for Personalized Medicine in Oncology in Canada","year":2013,"lang":"en","type":"article","venue":"Current Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Centre for Reproductive Medicine; Vancouver General Hospital; University of British Columbia; Princess Margaret Cancer Centre; BC Cancer Agency; Jewish General Hospital; University Health Network; University of Toronto; University of Calgary; McGill University; University of Alberta","funders":"U.S. Food and Drug Administration; National Comprehensive Cancer Network","keywords":"Personalized medicine; Medicine; Precision medicine; Context (archaeology); Psychological intervention; SAFER; Genetic testing; Cancer prevention; Health care; MEDLINE; Alternative medicine; Family medicine; Cancer; Bioinformatics; Internal medicine; Nursing; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01786306,0.0005485346,0.0008025619,0.002791496,0.0138282,0.01322236,0.004130009,0.009570263,0.008465969],"category_scores_gemma":[0.0781562,0.0006066976,0.001574487,0.006060879,0.007380057,0.005160221,0.006750413,0.01000846,0.000934524],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1412076,"about_ca_system_score_gemma":0.5679832,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9791915,"about_ca_topic_score_gemma":0.9900322,"domain_scores_codex":[0.9706694,0.008479547,0.002417136,0.001120792,0.0106439,0.006669207],"domain_scores_gemma":[0.9062089,0.01789915,0.003581919,0.001447879,0.03951965,0.0313425],"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":[0.0001121003,0.0001027735,0.02245609,0.001955093,0.00009869854,0.0009857818,0.004248906,0.001368939,0.0003454577,0.04808363,0.7295024,0.1907401],"study_design_scores_gemma":[0.0001879411,0.00008039347,0.0398711,0.008489547,0.000248935,0.0006315687,0.0253329,0.002249708,0.0004073071,0.03585282,0.8862669,0.000380781],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.002388466,0.01261387,0.0005622944,0.9655617,0.001463458,0.00010745,0.0002927186,0.00005616858,0.01695389],"genre_scores_gemma":[0.209035,0.09329441,0.02482159,0.6500441,0.003534801,0.0003599152,0.001446896,0.0001651183,0.01729807],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.8587924,"threshold_uncertainty_score":0.9960775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05601928979221446,"score_gpt":0.3685454927805287,"score_spread":0.3125262029883142,"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."}}