{"id":"W2946394381","doi":"10.1002/sim.8170","title":"Partitioning of time trends in prevalence and mortality of lung cancer","year":2019,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Aging","funders":"National Institute on Aging; Shandong Academy of Sciences","keywords":"Lung cancer; Incidence (geometry); Medicine; Mortality rate; Demography; Epidemiology; Relative survival; Adenocarcinoma; Cancer; Disease; Stage (stratigraphy); Internal medicine; Cancer registry; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005816236,0.0003829729,0.0003241505,0.00276902,0.0002931682,0.0009084884,0.0004946907,0.0003011576,0.001076959],"category_scores_gemma":[0.0129379,0.0002000623,0.0012278,0.00218026,0.0003386821,0.0005572214,0.0008756841,0.0003786982,0.0002566942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101995,"about_ca_system_score_gemma":0.0008446605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009391805,"about_ca_topic_score_gemma":0.006922302,"domain_scores_codex":[0.9954259,0.002178685,0.000357978,0.001048285,0.0006862177,0.000302951],"domain_scores_gemma":[0.9944854,0.00216776,0.001558972,0.0006273725,0.001000275,0.0001602689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000240997,0.00002452755,0.9602616,0.000188891,0.0006074678,0.00008167333,0.0007948924,0.004691528,0.001574644,0.001402136,0.0005031981,0.02962838],"study_design_scores_gemma":[0.000005184571,0.0001191381,0.9910787,0.00003423623,0.00008652826,0.0001516245,0.0004615167,0.005295245,0.0004077003,0.001013792,0.001331427,0.00001498907],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712758,0.001323444,0.01998626,0.0003633146,0.00003464405,0.0003932441,0.00379805,0.0000605023,0.002764736],"genre_scores_gemma":[0.9902911,0.0002823022,0.005201979,0.00005072852,0.0000178125,0.0001384608,0.003668974,0.00001711196,0.0003315454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009391805,"threshold_uncertainty_score":0.03075957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04763779418145317,"score_gpt":0.4139136475891051,"score_spread":0.366275853407652,"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."}}