{"id":"W4396717035","doi":"10.14740/wjon1831","title":"Deciphering Trends in Cancer Mortality: A Comprehensive Analysis of Brazilian Data From 1979 to 2021 With Emphasis on Breast and Prostate Cancers","year":2024,"lang":"en","type":"article","venue":"World Journal of Oncology","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Universidade do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Medicine; Prostate cancer; Cancer; Demography; Breast cancer; Mortality rate; Population; China; Cause of death; Gerontology; Environmental health; Pathology; Geography; Internal medicine; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001587731,0.000303385,0.0004582502,0.003586316,0.0002684844,0.0005785784,0.0003511931,0.0001974055,0.0005802565],"category_scores_gemma":[0.00409901,0.0001387296,0.0008084876,0.005191574,0.0001673724,0.0004253878,0.0007377632,0.0003042102,0.0001569894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001589793,"about_ca_system_score_gemma":0.002338646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.17747,"about_ca_topic_score_gemma":0.2543757,"domain_scores_codex":[0.9995283,0.00009581268,0.0000804745,0.00008986033,0.0001285364,0.00007704244],"domain_scores_gemma":[0.9983544,0.0002692789,0.0006216837,0.0001569691,0.0004833146,0.0001143214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002867594,0.00001348788,0.9788454,0.0001476158,0.0001550377,0.0000721118,0.0003700068,0.0005887825,0.0003530158,0.0002559694,0.001137765,0.01803202],"study_design_scores_gemma":[0.000001912493,0.00001885972,0.9929485,0.00008467548,0.00006913464,0.00009512497,0.000493834,0.0006196187,0.0001601661,0.00008539024,0.005416314,0.000006412849],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9418852,0.00866974,0.002101233,0.001473182,0.00005325301,0.00009992646,0.04102641,0.00005548516,0.004635544],"genre_scores_gemma":[0.9759487,0.003099259,0.001582366,0.0001104524,0.00002968,0.0000617203,0.01881998,0.00001262027,0.0003351806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.17747,"threshold_uncertainty_score":0.352874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.130187664557649,"score_gpt":0.446624922635202,"score_spread":0.316437258077553,"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."}}