{"id":"W2162891254","doi":"10.1093/epirev/mxq021","title":"Measuring Mortality Reductions in Cancer Screening Trials","year":2011,"lang":"en","type":"article","venue":"Epidemiologic Reviews","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University","funders":"Department of Epidemiology, Biostatistics and Occupational Health, McGill University; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Medicine; Cancer; Colorectal cancer; Breast cancer; Randomized controlled trial; Natural history; Clinical trial; Prostate cancer; Cancer screening; Mortality rate; Disease; Demography; Intensive care medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01408041,0.0001785069,0.001483812,0.0001279143,0.00007124883,0.000004350624,0.00008571738,0.0001297234,0.0005227764],"category_scores_gemma":[0.01246664,0.0001198181,0.0003840624,0.0004192261,0.0000578812,0.00008247966,0.00003273251,0.0003749071,0.00003641103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001297894,"about_ca_system_score_gemma":0.00004832395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003624691,"about_ca_topic_score_gemma":0.000419108,"domain_scores_codex":[0.9962112,0.001623766,0.001356441,0.000403308,0.0001153393,0.0002899259],"domain_scores_gemma":[0.9986655,0.0003076172,0.0004833482,0.0003696926,0.00005090456,0.0001229584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001053355,0.0001321775,0.4900031,0.0002396683,0.000123212,0.0000199997,0.0004272847,0.00006108537,0.0009514533,0.0001813515,0.005676527,0.5011308],"study_design_scores_gemma":[0.0007724991,0.0006246266,0.9272127,0.001158718,0.0002649267,0.00005278566,0.00008010083,0.0002824586,0.001037746,0.001252693,0.06700137,0.0002594113],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7661877,0.1777616,0.01753747,0.001983031,0.0017508,0.003693659,0.000009526187,0.0003704565,0.03070569],"genre_scores_gemma":[0.940051,0.03728103,0.01935017,0.001036258,0.0007556172,0.0009803597,0.00000888709,0.00002008203,0.0005165766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5008714,"threshold_uncertainty_score":0.9958518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7672342594608328,"score_gpt":0.4809905079133991,"score_spread":0.2862437515474337,"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."}}