{"id":"W2018483104","doi":"10.1136/bmj.g1403","title":"Too much mammography","year":2014,"lang":"en","type":"letter","venue":"BMJ","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mammography; Computer science; Data science; Medical physics; Medicine; Information retrieval; Breast cancer; Cancer; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006687189,0.0005962473,0.001292862,0.001022936,0.001727279,0.001972101,0.001170982,0.0115377,0.03422612],"category_scores_gemma":[0.04983684,0.0004567722,0.00142542,0.0009241201,0.002083991,0.003482061,0.001223354,0.0150803,0.009695488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00321044,"about_ca_system_score_gemma":0.002194703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005761973,"about_ca_topic_score_gemma":0.007282886,"domain_scores_codex":[0.9924151,0.002882509,0.0008736346,0.0007552646,0.002457777,0.0006156978],"domain_scores_gemma":[0.973353,0.01765905,0.001889925,0.001300084,0.003330264,0.002467652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006959348,0.0002081659,0.007369558,0.001389612,0.0001490456,0.00156046,0.0002316615,0.0001289437,0.0008351703,0.009126237,0.7890794,0.1892259],"study_design_scores_gemma":[0.000705733,0.0007496257,0.01561016,0.005791816,0.0002269085,0.008813619,0.0006166665,0.0002831885,0.0006459426,0.02035637,0.9461146,0.00008531917],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"editorial","genre_scores_codex":[0.002718601,0.01711727,0.0005594422,0.9411688,0.01851117,0.00005151747,0.0001961371,0.00006799339,0.01960908],"genre_scores_gemma":[0.02818242,0.01418558,0.0005170462,0.91497,0.03498086,0.00006680045,0.0001868722,0.00003924502,0.006871184],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.03422612,"threshold_uncertainty_score":0.1144978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09517596392349001,"score_gpt":0.3627440778508027,"score_spread":0.2675681139273127,"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."}}