{"id":"W4402917235","doi":"10.1109/cvprw63382.2024.00408","title":"BMAD: Benchmarks for Medical Anomaly Detection","year":2024,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Anomaly detection; Computer science; Artificial intelligence","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":[0.009667878,0.004058958,0.001722036,0.009733874,0.001261561,0.004006834,0.007643678,0.00367384,0.006979063],"category_scores_gemma":[0.04585392,0.0008830273,0.001809149,0.009764142,0.001124623,0.003203484,0.004114671,0.002578894,0.008109467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003030479,"about_ca_system_score_gemma":0.003412289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01176674,"about_ca_topic_score_gemma":0.01277694,"domain_scores_codex":[0.9832171,0.004029673,0.002639371,0.002142333,0.00720322,0.0007683119],"domain_scores_gemma":[0.977483,0.009968114,0.001482241,0.003846112,0.006261333,0.0009592095],"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":[0.00111002,0.0008300989,0.005991322,0.004218713,0.0004025472,0.000261337,0.0001840615,0.05840382,0.005195902,0.01227629,0.5815665,0.3295594],"study_design_scores_gemma":[0.001104116,0.0008417747,0.01419904,0.001144606,0.0002720792,0.001614597,0.0003371056,0.4814062,0.03643609,0.04111042,0.4212498,0.0002841682],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07416885,0.04033259,0.3403804,0.006658288,0.003646858,0.003637258,0.240396,0.2280731,0.06270666],"genre_scores_gemma":[0.1106285,0.005033239,0.4364613,0.001364636,0.0004030927,0.003170452,0.4274296,0.009141886,0.006367308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01176674,"threshold_uncertainty_score":0.05112922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006793689405046456,"score_gpt":0.2734587328745697,"score_spread":0.2666650434695232,"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."}}