{"id":"W2919816726","doi":"10.1109/cspis.2018.8642713","title":"Data Analytics Methods for Anomaly Detection: Evolution and Recommendations","year":2018,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Anomaly detection; Computer science; Big data; Anomaly (physics); Support vector machine; Data mining; Analytics; Artificial intelligence; Artificial neural network; Machine learning; Data science","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":[0.007738885,0.001454591,0.001542861,0.005845074,0.0006596281,0.003325383,0.002562262,0.001614646,0.001839804],"category_scores_gemma":[0.02696922,0.0007036502,0.001034597,0.0050454,0.001067542,0.006528296,0.001424896,0.003410339,0.001282425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001240143,"about_ca_system_score_gemma":0.001068249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002883767,"about_ca_topic_score_gemma":0.003262398,"domain_scores_codex":[0.9938964,0.001817364,0.0004422062,0.0008371269,0.002866251,0.0001405538],"domain_scores_gemma":[0.9798809,0.01093759,0.001381839,0.002412963,0.005037768,0.0003487404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001232957,0.0003767531,0.01786081,0.0007054268,0.0003427096,0.00008739041,0.0003148202,0.0394084,0.002176195,0.03759911,0.01803153,0.8829736],"study_design_scores_gemma":[0.00003608458,0.0001276728,0.003281124,0.0003505366,0.00008739555,0.0001845151,0.0003551346,0.8815985,0.003109637,0.08962652,0.02117552,0.00006746774],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008928048,0.006713703,0.9748824,0.004879837,0.0003506018,0.0002275445,0.0003534588,0.001187803,0.002476606],"genre_scores_gemma":[0.2710494,0.01137247,0.709682,0.0008535156,0.001268532,0.0005284987,0.001485842,0.0002162424,0.003543423],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007738885,"threshold_uncertainty_score":0.04092765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09630863901501527,"score_gpt":0.4095064417637113,"score_spread":0.313197802748696,"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."}}