{"id":"W3036595858","doi":"10.5489/cuaj.6716","title":"Determining Generalizability of the Canadian Kidney Cancer information system (CKCis) to the Entire Canadian Kidney Cancer Population","year":2020,"lang":"en","type":"article","venue":"Canadian Urological Association Journal","topic":"Renal cell carcinoma treatment","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; Université de Montréal; University of Manitoba; University of British Columbia; Université Laval; University of Alberta; Université de Sherbrooke; Western University; University of Toronto; Dalhousie University; McGill University; University of Ottawa; University of Calgary; London Health Sciences Centre; McMaster University","funders":"Social Sciences and Humanities Research Council of Canada; Canadian Institutes of Health Research","keywords":"Medicine; Cancer registry; Kidney cancer; Cancer; Cohort; Population; Incidence (geometry); Kidney disease; Prospective cohort study; Renal cell carcinoma; Cohort study; Demography; Internal medicine; Environmental health","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":[0.006837957,0.0003622674,0.0004137783,0.003587908,0.002908683,0.00206218,0.001859638,0.0004407367,0.004179092],"category_scores_gemma":[0.04042472,0.0003382142,0.0008917749,0.006620544,0.000931537,0.0007219793,0.002036202,0.0006949529,0.0004197665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02098478,"about_ca_system_score_gemma":0.03429142,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9788126,"about_ca_topic_score_gemma":0.9734248,"domain_scores_codex":[0.9900624,0.001014592,0.0007163251,0.001477706,0.005322136,0.001406991],"domain_scores_gemma":[0.9843407,0.001724063,0.002324803,0.001427755,0.009078524,0.00110413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000622048,0.00001481071,0.9761341,0.0001040676,0.0001629027,0.00003580108,0.0009161751,0.0003492971,0.0001009798,0.0005980954,0.01082081,0.01070085],"study_design_scores_gemma":[0.00001939654,0.00003199192,0.9857743,0.0001310052,0.0000924869,0.00006722376,0.001405094,0.000855101,0.0001362282,0.0002040572,0.01126366,0.00001942793],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8307103,0.002491536,0.003648652,0.005879796,0.0003274078,0.001315107,0.1092692,0.0002005026,0.04615748],"genre_scores_gemma":[0.9778131,0.0006383107,0.001206887,0.0009358803,0.00005259414,0.0003562387,0.01793038,0.00003336296,0.001033212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02118742,"threshold_uncertainty_score":0.152256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02336058013677052,"score_gpt":0.2366220192688669,"score_spread":0.2132614391320964,"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."}}