{"id":"W2894003238","doi":"10.1200/jgo.18.46100","title":"Essential TNM: A Means to Collect Stage Data in Population-Based Registries in Low- and Middle-Income Countries","year":2018,"lang":"en","type":"article","venue":"Journal of Global Oncology","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"","keywords":"Medicine; Cancer; Context (archaeology); Disease; Stage (stratigraphy); Population; Cancer registry; Incidence (geometry); Internal medicine; Environmental health","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":[0.08877534,0.000730716,0.000979047,0.01033263,0.0008217287,0.002404344,0.001926817,0.0007584423,0.007972763],"category_scores_gemma":[0.1604955,0.0007266146,0.001149065,0.01018303,0.0006224135,0.003271908,0.004844442,0.0009752761,0.002303239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002598631,"about_ca_system_score_gemma":0.01323281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005840183,"about_ca_topic_score_gemma":0.005685721,"domain_scores_codex":[0.9365495,0.040268,0.01295062,0.002512756,0.006564315,0.001154683],"domain_scores_gemma":[0.895025,0.03115068,0.02230318,0.02206203,0.02554933,0.00390983],"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":[0.0009340749,0.0002923453,0.2892669,0.003775624,0.0003912298,0.000430832,0.00407788,0.004644321,0.002716888,0.02267072,0.1526093,0.5181898],"study_design_scores_gemma":[0.001142942,0.001357968,0.5053486,0.005063449,0.0004908145,0.00107009,0.004046968,0.02102936,0.004828981,0.01454932,0.4408215,0.0002501443],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.115689,0.00204465,0.485894,0.01087088,0.001593353,0.07389427,0.2328784,0.01012916,0.06700642],"genre_scores_gemma":[0.1663447,0.0009964043,0.7003605,0.001062537,0.0003154802,0.04818339,0.0785116,0.0004953081,0.003730213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08877534,"threshold_uncertainty_score":0.4694945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06772132120689824,"score_gpt":0.3966249766568848,"score_spread":0.3289036554499866,"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."}}