{"id":"W154235046","doi":"10.1007/978-3-319-11653-2_5","title":"Streaming Model Transformations By Complex Event Processing","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Computer science; Complex event processing; Streaming data; Event (particle physics); Model transformation; Transformation (genetics); Class (philosophy); Context (archaeology); Process (computing); Stream processing; Data mining; Data stream; Theoretical computer science; Artificial intelligence; Distributed computing; Programming language","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":[0.0004718148,0.0006814909,0.0006253437,0.0004153536,0.0002244286,0.0008301012,0.0009367763,0.0004243796,0.006256372],"category_scores_gemma":[0.002005411,0.0004603744,0.0008648632,0.0006910266,0.0003725601,0.001648538,0.001029327,0.001373006,0.0018492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004363477,"about_ca_system_score_gemma":0.0003782102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00255241,"about_ca_topic_score_gemma":0.002340052,"domain_scores_codex":[0.9996817,0.00006155219,0.0000236952,0.00009913685,0.0001076594,0.00002629627],"domain_scores_gemma":[0.9993437,0.0003016688,0.00003658751,0.0002114497,0.00008520532,0.00002139927],"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":[0.0002281764,0.00009733399,0.0004368101,0.0001419556,0.00007618485,0.0001919317,0.0001285648,0.4717051,0.01790963,0.1174957,0.007555436,0.3840332],"study_design_scores_gemma":[0.000005388221,0.00001136412,0.00005248949,0.000002571066,0.000005389491,0.00002976863,0.000006958136,0.9526919,0.002996988,0.04181389,0.002378665,0.000004674707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002360701,0.00004671824,0.9956404,0.00003408302,0.00002276513,0.00001592692,0.00009065527,0.0009967898,0.0007919259],"genre_scores_gemma":[0.2946257,0.0004335398,0.6913285,0.0000847109,0.00009990793,0.0001640003,0.001862767,0.001020945,0.01037997],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006256372,"threshold_uncertainty_score":0.02092963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03245666733986978,"score_gpt":0.2657976987796531,"score_spread":0.2333410314397834,"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."}}