{"id":"W2898613396","doi":"10.1109/asonam.2018.8508299","title":"A Statistical Framework for Handling Network Anomalies","year":2018,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Computer science; Node (physics); Data mining; Feature (linguistics); Feature vector; Similarity (geometry); Exploit; Measure (data warehouse); Task (project management); Cluster analysis; Dirichlet distribution; Perspective (graphical); Statistical model; Artificial intelligence; Pattern recognition (psychology); Image (mathematics); Mathematics; Engineering","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":[0.003673052,0.001319287,0.001329433,0.006339531,0.0009895891,0.002100471,0.002654029,0.001546431,0.001519191],"category_scores_gemma":[0.01487659,0.0007887295,0.001630339,0.003772706,0.002092881,0.003727579,0.001972748,0.002363263,0.0006878279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001538215,"about_ca_system_score_gemma":0.001683944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005382727,"about_ca_topic_score_gemma":0.00385032,"domain_scores_codex":[0.9973177,0.0008112114,0.0001790062,0.0006854081,0.0008692808,0.0001372833],"domain_scores_gemma":[0.9918849,0.004825772,0.0009982747,0.0009481005,0.001121212,0.0002217359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000421132,0.00007234859,0.004218318,0.0001459086,0.0002021422,0.000403903,0.0002649904,0.4761836,0.005356812,0.4084961,0.003481791,0.1011319],"study_design_scores_gemma":[0.000005186438,0.00001893195,0.0004940121,0.00001372451,0.00001955405,0.0001158427,0.00002584533,0.8580111,0.0006129317,0.1369961,0.003660984,0.00002580103],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007975828,0.00007165175,0.9985731,0.00008001903,0.00001469903,0.0000106577,0.00005126838,0.0001940717,0.0002069085],"genre_scores_gemma":[0.2002048,0.0008869761,0.7945168,0.0002593162,0.0006363129,0.0003598682,0.0008146495,0.0003449471,0.001976295],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006339531,"threshold_uncertainty_score":0.01942515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01889889423956525,"score_gpt":0.3248309973232339,"score_spread":0.3059321030836686,"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."}}