{"id":"W3121030001","doi":"10.1007/s10278-020-00407-0","title":"DeepCAT: Deep Computer-Aided Triage of Screening Mammography","year":2021,"lang":"en","type":"article","venue":"Journal of Digital Imaging","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Triage; Mammography; Medicine; Artificial intelligence; Deep learning; Medical physics; Breast cancer; Radiology; Digital mammography; Prioritization; Breast cancer screening; Computer science; Cancer; Medical emergency; Internal medicine","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":[0.000359944,0.000840225,0.0007034909,0.001216824,0.000285297,0.0007780441,0.0009492216,0.0006968693,0.009122805],"category_scores_gemma":[0.002084016,0.0004611269,0.0005237897,0.0006843836,0.0001267027,0.0005145469,0.00160126,0.0006397171,0.002597006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003709513,"about_ca_system_score_gemma":0.0009678206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007298261,"about_ca_topic_score_gemma":0.02011511,"domain_scores_codex":[0.9997562,0.0000473119,0.00001615526,0.00006287572,0.00007299347,0.00004446734],"domain_scores_gemma":[0.9995975,0.0001967446,0.0000301164,0.00005457517,0.00007591014,0.00004518791],"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":[0.001786968,0.0003574359,0.01436761,0.0003179801,0.0003592334,0.0004986239,0.0001097781,0.01575541,0.02247442,0.001548861,0.12836,0.8140637],"study_design_scores_gemma":[0.0003411638,0.0004617703,0.01997065,0.0001240168,0.0001708669,0.001540893,0.0001308183,0.8956037,0.02962321,0.008411323,0.0435034,0.0001181527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2112189,0.00580181,0.5751673,0.002444932,0.001165148,0.001190038,0.04787873,0.1427962,0.01233696],"genre_scores_gemma":[0.5746371,0.001271527,0.3754921,0.001389904,0.0003141172,0.0006961584,0.02982367,0.002145784,0.01422955],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009122805,"threshold_uncertainty_score":0.03051889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501457882796578,"score_gpt":0.2643472255568894,"score_spread":0.2493326467289236,"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."}}