{"id":"W4214863304","doi":"10.3390/curroncol29030136","title":"The OncoSim-Breast Cancer Microsimulation Model","year":2022,"lang":"en","type":"article","venue":"Current Oncology","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; Public Health Ontario; University of Toronto; Statistics Canada; Canadian Partnership Against Cancer","funders":"","keywords":"Breast cancer; Medicine; Cancer registry; Population; Breast cancer screening; Cancer; Ductal carcinoma; Oncology; Incidence (geometry); Demography; Internal medicine; Mammography; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00254318,0.00009382259,0.000159195,0.0001287217,0.001164518,0.00009699083,0.0006158645,0.00003536649,0.0003221747],"category_scores_gemma":[0.0001481047,0.00006145376,0.0001062924,0.0005536432,0.00009683742,0.0001036209,0.000222988,0.0002910073,0.00004465452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000217739,"about_ca_system_score_gemma":0.000252407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002168329,"about_ca_topic_score_gemma":0.0001079002,"domain_scores_codex":[0.9976982,0.0003844376,0.0004798155,0.000343783,0.0008420755,0.0002516412],"domain_scores_gemma":[0.9982443,0.0007958131,0.0002743868,0.000348126,0.0002739966,0.00006338264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008748693,0.0001281805,0.005346138,0.000001054368,0.000006640768,5.816486e-7,0.0006033669,0.3647085,0.0001743206,0.003111387,0.02528136,0.600551],"study_design_scores_gemma":[0.000267914,0.00003695929,0.002302441,0.000001606128,0.00001087653,0.00000706218,0.0006745362,0.7118279,0.000002697026,0.02338896,0.2614104,0.00006855177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9231659,0.004634015,0.03988888,0.01832919,0.009012919,0.0004994238,0.0003177997,0.0001226902,0.004029223],"genre_scores_gemma":[0.9984294,0.0003148716,0.00008744403,0.0002470255,0.000106525,0.0001668348,0.00001333882,0.000008494248,0.0006261223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6004824,"threshold_uncertainty_score":0.8956645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.373549585537822,"score_gpt":0.5208954991273782,"score_spread":0.1473459135895562,"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."}}