{"id":"W4390145201","doi":"10.1002/cncr.35155","title":"Data‐driven optimization of version 9 American Joint Committee on Cancer staging system for anal cancer","year":2023,"lang":"en","type":"article","venue":"Cancer","topic":"Colorectal and Anal Carcinomas","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"National Cancer Institute","keywords":"Medicine; Stage (stratigraphy); Cancer; Proportional hazards model; Cancer staging; Survival analysis; Oncology; Anal cancer; AJCC staging system; Internal medicine; Staging system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009929355,0.0001144488,0.0003222905,0.0001293464,0.00007508804,0.000007600411,0.0001137655,0.00003088559,0.0001414312],"category_scores_gemma":[0.00002132985,0.00009588082,0.0000695394,0.0004541222,0.00006638009,0.00005809915,0.00007919616,0.00008987659,0.000005117628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003935931,"about_ca_system_score_gemma":0.0002176008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00272547,"about_ca_topic_score_gemma":0.0005545339,"domain_scores_codex":[0.9990725,0.00001936303,0.0001963899,0.0002805584,0.0002217485,0.0002094368],"domain_scores_gemma":[0.9992982,0.00004237743,0.0001488364,0.000272181,0.0001510661,0.00008736336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003405735,0.0001588989,0.2459543,0.004029708,0.0007461707,0.00005707018,0.001234768,0.4851297,0.02258177,0.000185118,0.1463913,0.09012552],"study_design_scores_gemma":[0.003146963,0.0007544634,0.1175228,0.00262722,0.0005730306,0.000002538881,0.002356576,0.8425449,0.009773835,0.0000041466,0.0203179,0.0003756057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918868,0.0005930136,0.0006484604,0.002847582,0.000718258,0.0005520807,0.002155813,0.0001186956,0.0004793036],"genre_scores_gemma":[0.9975638,0.0005388067,0.0002133515,0.0002770077,0.0004316085,0.0001677833,0.0003183208,0.00002688,0.0004624451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3574152,"threshold_uncertainty_score":0.4120114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07719968965886945,"score_gpt":0.3427930078502065,"score_spread":0.265593318191337,"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."}}