{"id":"W2070864209","doi":"10.1145/1118537.1123064","title":"Performance modeling and prediction of enterprise JavaBeans with layered queuing network templates","year":2005,"lang":"en","type":"article","venue":"ACM SIGSOFT Software Engineering Notes","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Application server; Scalability; Server; Template; JavaBeans; Java; Component (thermodynamics); Queueing theory; Modular design; Operating system; Message queue; Component-based software engineering; Queue; Distributed computing; Software; Database; Software engineering; Software system; Computer network; 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":[0.00259486,0.0008126895,0.0005519855,0.0007290425,0.0002379704,0.001135144,0.001327002,0.0007968135,0.0004085726],"category_scores_gemma":[0.006602773,0.0004666356,0.0006166906,0.0006208703,0.0004098807,0.001038187,0.0004103725,0.0007016597,0.0001813804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002106939,"about_ca_system_score_gemma":0.001227873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02077137,"about_ca_topic_score_gemma":0.007293789,"domain_scores_codex":[0.9989442,0.0003790008,0.00006873837,0.0001660954,0.00030836,0.0001336528],"domain_scores_gemma":[0.997127,0.001401474,0.0004054692,0.0002923232,0.0006075468,0.0001661787],"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":[0.00005600365,0.00006438012,0.003215924,0.000009788092,0.00001351891,0.00001760352,0.00003169621,0.9887972,0.001749437,0.001697584,0.0001261094,0.004220686],"study_design_scores_gemma":[0.00000211184,0.000008564151,0.0003117364,5.832844e-7,0.000001780469,0.000001506141,0.000001209075,0.9990262,0.0003605795,0.0002530395,0.00002975414,0.000003041343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6378314,0.0001440421,0.3579613,0.0001789586,0.00004595739,0.00007439806,0.0002410263,0.001651139,0.001871928],"genre_scores_gemma":[0.972711,0.00006161218,0.0263132,0.00001586968,0.000008145114,0.00003967275,0.0001975765,0.0000662158,0.0005867299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02077137,"threshold_uncertainty_score":0.04130095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00986127314587406,"score_gpt":0.1925936872529448,"score_spread":0.1827324141070707,"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."}}