{"id":"W3140302147","doi":"10.1016/j.cag.2021.03.004","title":"ProSeCo: Visual analysis of class separation measures and dataset characteristics","year":2021,"lang":"en","type":"article","venue":"Computers & Graphics","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Österreichische Forschungsförderungsgesellschaft; NÖ Forschungs- und Bildungsges.m.b.H.; Deutsche Forschungsgemeinschaft","keywords":"Separation (statistics); Computer science; Skewness; Class (philosophy); Visualization; Dimensionality reduction; Artificial intelligence; Visual analytics; Pattern recognition (psychology); Data mining; Machine learning; Statistics; 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":[0.004910466,0.001948062,0.001092097,0.00741811,0.000813895,0.005091131,0.001573461,0.001183328,0.01101988],"category_scores_gemma":[0.01979655,0.0005795018,0.001186573,0.003814604,0.0008167572,0.004260437,0.004638835,0.003241573,0.00198433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007669174,"about_ca_system_score_gemma":0.001299184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002155429,"about_ca_topic_score_gemma":0.002744569,"domain_scores_codex":[0.9979783,0.0004916274,0.0001781693,0.0003159396,0.0008732727,0.0001627342],"domain_scores_gemma":[0.9875382,0.006586379,0.001291872,0.001517515,0.002613281,0.0004527904],"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":[0.001625384,0.0005300128,0.01972188,0.002757675,0.0004858782,0.0005407164,0.004191663,0.03783794,0.04163869,0.03837441,0.2034149,0.6488808],"study_design_scores_gemma":[0.0004060828,0.0005798798,0.0302993,0.0009087297,0.0002062399,0.00120406,0.002555019,0.6284981,0.05676576,0.1215042,0.1565444,0.0005281218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0365959,0.0009235243,0.8815652,0.00172146,0.0004608941,0.0004822302,0.01455665,0.05663892,0.00705513],"genre_scores_gemma":[0.1800702,0.000853462,0.794867,0.0005051611,0.0002846912,0.001034701,0.01215658,0.007851679,0.002376524],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01101988,"threshold_uncertainty_score":0.03686517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01852406985079736,"score_gpt":0.3002955657759921,"score_spread":0.2817714959251947,"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."}}