{"id":"W1990106316","doi":"10.1145/2487575.2487676","title":"Subsampling for efficient and effective unsupervised outlier detection ensembles","year":2013,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":190,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Outlier; Anomaly detection; Detector; Computer science; Intuition; Artificial intelligence; Ensemble learning; Pattern recognition (psychology); Data mining; Local outlier factor; Machine learning","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":[0.004397594,0.001085429,0.00208329,0.001642634,0.0008993128,0.001355644,0.001556151,0.001212071,0.001028787],"category_scores_gemma":[0.01822819,0.0006535212,0.001382973,0.001465161,0.0009387875,0.002345606,0.002714256,0.002097157,0.000645107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006497186,"about_ca_system_score_gemma":0.001046367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0019139,"about_ca_topic_score_gemma":0.002733077,"domain_scores_codex":[0.9964609,0.001181239,0.0002499112,0.0006896215,0.001125486,0.0002929032],"domain_scores_gemma":[0.9892005,0.005111828,0.0008953003,0.002317929,0.002116363,0.0003581346],"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":[0.0002942238,0.0001815671,0.006641787,0.0001363412,0.0003136851,0.0001857874,0.0003706391,0.5842071,0.0187937,0.02997193,0.00396344,0.3549399],"study_design_scores_gemma":[0.000007728338,0.00004952218,0.0004534175,0.000008404496,0.00001724183,0.00006259923,0.00002491132,0.9818476,0.003661489,0.01273903,0.00111393,0.00001407238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01277247,0.0001416528,0.9862163,0.00007807491,0.00002321847,0.00002885905,0.00005121626,0.0004206258,0.0002675735],"genre_scores_gemma":[0.3922455,0.0002706156,0.6047778,0.0001841911,0.0001502517,0.0002074725,0.0007147711,0.0002122327,0.001237239],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004397594,"threshold_uncertainty_score":0.02325702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008596002049371925,"score_gpt":0.2288586689921176,"score_spread":0.2202626669427457,"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."}}