{"id":"W4226378137","doi":"10.1016/j.media.2022.102526","title":"Constrained unsupervised anomaly segmentation","year":2022,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"European Regional Development Fund; Generalitat Valenciana; European Commission","keywords":"Computer science; Segmentation; Anomaly detection; Constraint (computer-aided design); Artificial intelligence; Hyperparameter; Regularization (linguistics); Pattern recognition (psychology); Machine learning; Mathematics","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":[0.0009712359,0.00139329,0.001676942,0.002212179,0.0005891038,0.001601834,0.002645111,0.002134372,0.002393684],"category_scores_gemma":[0.003460418,0.000691165,0.001605487,0.00178079,0.001649141,0.001699313,0.002254564,0.001396722,0.0009806256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001065287,"about_ca_system_score_gemma":0.001963688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004405566,"about_ca_topic_score_gemma":0.006945166,"domain_scores_codex":[0.9988605,0.0002008365,0.00005339981,0.0004691701,0.0002704052,0.0001457975],"domain_scores_gemma":[0.9986675,0.0005495641,0.0001939362,0.0002848856,0.0002412442,0.00006299176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002565031,0.0001264503,0.002926444,0.0003361144,0.0002475167,0.0003773999,0.0003740975,0.5407684,0.03311475,0.03649316,0.008577762,0.3764014],"study_design_scores_gemma":[0.000008361483,0.0000177787,0.0004768899,0.00001289693,0.00001574494,0.0001441229,0.00002083905,0.9724524,0.004438243,0.0206054,0.001792738,0.00001458643],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01143512,0.0002379728,0.985359,0.0001407042,0.00002180716,0.00004554304,0.0001806051,0.001565523,0.001013748],"genre_scores_gemma":[0.4373457,0.0005442022,0.5509437,0.0004569323,0.000214081,0.0002970441,0.002449965,0.001457584,0.006290881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004405566,"threshold_uncertainty_score":0.008759856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006985585779932297,"score_gpt":0.2591613300058138,"score_spread":0.2521757442258815,"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."}}