{"id":"W2759978833","doi":"10.9778/cmajo.20170030","title":"Breast cancer survival by molecular subtype: a population-based analysis of cancer registry data","year":2017,"lang":"en","type":"article","venue":"CMAJ Open","topic":"Breast Cancer Treatment Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":408,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cancer Care Ontario","funders":"Cancer Care Ontario","keywords":"Medicine; Hazard ratio; Breast cancer; Oncology; Internal medicine; Proportional hazards model; Cancer; Comorbidity; Estrogen receptor; Cancer registry; Confidence interval; Population; Stage (stratigraphy); Progesterone receptor; Gynecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002146381,0.000225368,0.0004611485,0.001404328,0.0004591481,0.0006108077,0.0006881744,0.0002313871,0.001096249],"category_scores_gemma":[0.004439644,0.0002967923,0.0007666628,0.004191335,0.0003722216,0.0003427459,0.0006678473,0.0003346622,0.0001962388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003615024,"about_ca_system_score_gemma":0.003713223,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5475324,"about_ca_topic_score_gemma":0.598574,"domain_scores_codex":[0.9985108,0.0003577059,0.0001500036,0.0003190015,0.0004319875,0.0002305456],"domain_scores_gemma":[0.9966222,0.0005354002,0.001548073,0.0004953126,0.0005540351,0.0002449994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004371157,0.000004021109,0.9988481,0.00001176231,0.00006913501,0.0000188244,0.00006061116,0.00006714753,0.00004777821,0.0000100579,0.0001638086,0.000655002],"study_design_scores_gemma":[0.000005254375,0.00001234265,0.9993773,0.000005464165,0.00003351199,0.0000419456,0.00006448261,0.0001798894,0.00001302156,0.000007318181,0.0002572534,0.000002326839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929321,0.0003166504,0.0002369014,0.00007659842,0.000003208278,0.0000277832,0.006050328,0.00001272494,0.0003435815],"genre_scores_gemma":[0.9952278,0.0001590333,0.0002119523,0.00001674158,0.000004562335,0.00002247464,0.00426407,0.000003733447,0.00008970235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5475324,"threshold_uncertainty_score":0.9102646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03933172059223837,"score_gpt":0.3662867462070122,"score_spread":0.3269550256147739,"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."}}