{"id":"W383165039","doi":"","title":"Cancer incidence in Canada: trends and projections (1983-2032).","year":2015,"lang":"en","type":"article","venue":"PubMed","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada","funders":"","keywords":"Cancer incidence; Cancer; Political science; Library science; Geography; Humanities; Demography; Regional science; Population; Sociology; Medicine; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0007716178,0.0008201438,0.0003828977,0.004653559,0.001278392,0.001464948,0.0008810456,0.0007264059,0.00996323],"category_scores_gemma":[0.002037408,0.0003785547,0.001190029,0.01207267,0.0002695437,0.0006875251,0.0007426922,0.001200738,0.004541759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03816791,"about_ca_system_score_gemma":0.06885314,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9878379,"about_ca_topic_score_gemma":0.9906192,"domain_scores_codex":[0.9992459,0.00003135301,0.00004336658,0.00004770461,0.0004670852,0.0001646992],"domain_scores_gemma":[0.9979486,0.00004783234,0.000116727,0.00002436099,0.001696557,0.0001659738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002075112,0.00004478769,0.03712439,0.002156983,0.0001522157,0.0001223421,0.0003076862,0.003189893,0.0001883618,0.002376312,0.8206676,0.1334619],"study_design_scores_gemma":[0.00008039281,0.00006990432,0.3737178,0.001668608,0.0002899494,0.0002984798,0.0009057881,0.004786127,0.0005039778,0.00115849,0.6164584,0.00006194456],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.02581,0.05949239,0.00292606,0.01490399,0.001682509,0.0005122973,0.8120105,0.001556849,0.08110539],"genre_scores_gemma":[0.2592039,0.1475293,0.01264399,0.002882643,0.0006424603,0.0007970044,0.4908433,0.0003764009,0.08508103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03816791,"threshold_uncertainty_score":0.2769288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1294423783844582,"score_gpt":0.3194652397824155,"score_spread":0.1900228613979573,"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."}}