{"id":"W2998594312","doi":"10.1109/edoc.2019.00029","title":"Predictive Analytics for Event Stream Processing","year":2019,"lang":"en","type":"article","venue":"","topic":"Business Process Modeling and Analysis","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Complex event processing; Computer science; Stream processing; Event (particle physics); Workflow; Process mining; Process (computing); Business process; Analytics; Business process discovery; Business process management; Data mining; Computation; Business process modeling; Work in process; Distributed computing; Database; Programming language; 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":[0.002172176,0.001167396,0.0008200387,0.001844059,0.0004856048,0.00279244,0.00135557,0.0007143299,0.002419611],"category_scores_gemma":[0.006633598,0.0003679223,0.0009775707,0.002293664,0.0006091337,0.002785589,0.001289799,0.001854717,0.0008766598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008202189,"about_ca_system_score_gemma":0.0009688326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004375418,"about_ca_topic_score_gemma":0.00278354,"domain_scores_codex":[0.9984193,0.0003522188,0.0001527608,0.0002688902,0.0007170432,0.00008978443],"domain_scores_gemma":[0.9977952,0.001140237,0.0001757589,0.0004023289,0.0004223546,0.00006409256],"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":[0.0002748645,0.0002652328,0.005076839,0.0005023507,0.0002375343,0.0005028835,0.0002982859,0.37609,0.00673827,0.2167742,0.01799269,0.3752469],"study_design_scores_gemma":[0.000008894613,0.00001688302,0.0003201334,0.00003958799,0.0000196321,0.00005402323,0.00002912748,0.9159556,0.001821693,0.07481799,0.006902676,0.00001376657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003773284,0.0007394994,0.9885085,0.0004490354,0.00009438711,0.0001137292,0.0005955246,0.003214739,0.002511178],"genre_scores_gemma":[0.365993,0.00292287,0.6236235,0.0003543149,0.0004527096,0.0003295134,0.003318229,0.000345174,0.002660654],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004375418,"threshold_uncertainty_score":0.01148766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01657984723476217,"score_gpt":0.2417042614681306,"score_spread":0.2251244142333685,"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."}}