{"id":"W2735496645","doi":"10.1016/j.urolonc.2017.06.060","title":"Metastatic renal cell carcinoma: Patterns and predictors of metastases—A contemporary population-based series","year":2017,"lang":"en","type":"article","venue":"Urologic Oncology Seminars and Original Investigations","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":120,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Medicine; Renal cell carcinoma; Internal medicine; Chromophobe cell; Oncology; Odds ratio; Epidemiology; Disease; Hazard ratio; Kidney cancer; Logistic regression; Lung cancer; Population; Performance status; Cancer; Clear cell; Confidence interval","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002904354,0.0002331548,0.0005535576,0.000151662,0.0003813318,0.00003184958,0.000103683,0.000122202,0.00004387245],"category_scores_gemma":[0.0001669636,0.0001824324,0.00007708713,0.00006055216,0.0007677681,0.0001882228,0.00006321783,0.0002027419,0.000002089383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006712682,"about_ca_system_score_gemma":0.0003930425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007558219,"about_ca_topic_score_gemma":0.000101517,"domain_scores_codex":[0.9986899,0.0001538003,0.0004020817,0.0003608961,0.000179472,0.0002138547],"domain_scores_gemma":[0.9985405,0.0002377493,0.0004500143,0.0004016339,0.00008059149,0.0002895179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001896917,0.0001790517,0.996809,0.0001510722,0.00007288568,0.0003187189,0.000135561,0.00002255907,0.0007637737,0.0006611189,0.0005055754,0.0001909827],"study_design_scores_gemma":[0.002779515,0.005688792,0.9479003,0.00007442693,0.001120399,0.0003605702,0.0002202285,0.0003720279,0.009439017,0.001334173,0.03048676,0.0002238184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935811,0.001349327,0.00005007688,0.002831436,0.000097451,0.0004734166,0.0001956231,0.0000273207,0.001394301],"genre_scores_gemma":[0.979809,0.00006803085,0.01909202,0.0003364776,0.00005358167,0.00006332192,0.0002389474,0.00001499986,0.0003236088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04890873,"threshold_uncertainty_score":0.7439377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04462623261756779,"score_gpt":0.2982132785866013,"score_spread":0.2535870459690336,"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."}}