{"id":"W2990140997","doi":"10.1109/smc.2019.8914322","title":"A Neural Word Embedding Approach to System Trace Reconstruction","year":2019,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; TRACE (psycholinguistics); Data mining; Word embedding; Word (group theory); Intrusion detection system; Embedding; Hidden Markov model; Noise (video); Anomaly detection; Event (particle physics); Benchmark (surveying); Artificial intelligence; Algorithm","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":[0.0004490915,0.001080409,0.0006174772,0.001372345,0.0003106816,0.0006205358,0.0009352984,0.0008053834,0.00189117],"category_scores_gemma":[0.002855878,0.0004105536,0.0006237532,0.001347245,0.0004620928,0.002041806,0.0009815267,0.00159465,0.00102136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000488565,"about_ca_system_score_gemma":0.0007410633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007717993,"about_ca_topic_score_gemma":0.0107034,"domain_scores_codex":[0.9995327,0.0001030235,0.0000435796,0.0001450023,0.0001152451,0.0000604567],"domain_scores_gemma":[0.9988696,0.0004763965,0.0001166583,0.0002291836,0.0002665405,0.00004156107],"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":[0.0003068688,0.0002385993,0.003752986,0.0001778134,0.0001374935,0.0002267799,0.0001921978,0.3041036,0.01104218,0.008298126,0.005896262,0.6656271],"study_design_scores_gemma":[0.000005149952,0.00003768812,0.0002930953,0.000006267428,0.000007868999,0.00003725174,0.00001963763,0.9921604,0.002052184,0.004590403,0.0007813536,0.000008699994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04030235,0.0005562611,0.9542471,0.0002596523,0.0001314804,0.00005020813,0.0006315234,0.003001685,0.0008197003],"genre_scores_gemma":[0.6059291,0.0006389315,0.3819191,0.0002313946,0.0001517016,0.0001521112,0.003975637,0.0003703431,0.006631742],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007717993,"threshold_uncertainty_score":0.01534617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01271524036119229,"score_gpt":0.2372175083085267,"score_spread":0.2245022679473344,"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."}}