{"id":"W2902876869","doi":"10.1016/j.breast.2018.11.012","title":"Estimation of the benefit and harms of including clinical breast examination in an organized breast screening program","year":2018,"lang":"en","type":"article","venue":"The Breast","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Impact; Cancer Care Ontario; McMaster University; University of Toronto; Public Health Ontario","funders":"","keywords":"Medicine; Mammography; Breast cancer; Family history; Logistic regression; Hormone therapy; Breast density; Cohort; Breast cancer screening; Gynecology; Oncology; Mammography screening; Internal medicine; Hormone replacement therapy (female-to-male); Cancer","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":[0.009799739,0.0006650048,0.0007929633,0.001276654,0.0002790018,0.0008138759,0.0005855871,0.001342949,0.001662894],"category_scores_gemma":[0.03979721,0.0004295071,0.001831405,0.001164519,0.001014295,0.001195296,0.001341772,0.001241322,0.0001734882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476533,"about_ca_system_score_gemma":0.001373652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006014658,"about_ca_topic_score_gemma":0.007886013,"domain_scores_codex":[0.9900441,0.007824502,0.0004167136,0.0003588895,0.0008685069,0.0004872507],"domain_scores_gemma":[0.9729327,0.02114333,0.00347926,0.001073689,0.00067243,0.0006985967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.009602801,0.001592745,0.9209612,0.0004770314,0.002505391,0.000185,0.0002098805,0.01975599,0.000410957,0.001284884,0.0004791492,0.04253501],"study_design_scores_gemma":[0.0004866263,0.009782236,0.952438,0.0001696792,0.003343772,0.0003317902,0.0007457982,0.02823346,0.0006309543,0.002840914,0.0009544442,0.00004241252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9887879,0.002403114,0.001465486,0.001334567,0.00003366363,0.0002559633,0.0009338671,0.0000195691,0.004765855],"genre_scores_gemma":[0.9985117,0.0003594407,0.0006172339,0.0001064054,0.00002355879,0.00003976974,0.0001580055,0.000001046987,0.0001827494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009799739,"threshold_uncertainty_score":0.05182654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1109157872515085,"score_gpt":0.4085162621348857,"score_spread":0.2976004748833772,"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."}}