{"id":"W1562761433","doi":"10.1109/cloud.2015.39","title":"End-to-End QoS Prediction of Vertical Service Composition in the Cloud","year":2015,"lang":"en","type":"article","venue":"","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cloud computing; Quality of service; Computer science; Software; Service (business); Software as a service; Mobile QoS; End user; Matching (statistics); Distributed computing; Computer network; Software development; Operating system; Service provider","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004143216,0.00009991127,0.0001174226,0.0001113371,0.00004057258,0.00005360385,0.0008919625,0.00004946623,0.00001305956],"category_scores_gemma":[0.000005189863,0.00006641306,0.00002864559,0.000927052,0.00001436765,0.0002524474,0.0001993959,0.0001238745,0.00005829171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002329772,"about_ca_system_score_gemma":0.00004852024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008136689,"about_ca_topic_score_gemma":0.0007585763,"domain_scores_codex":[0.99874,0.0001454679,0.0002360648,0.0002388053,0.0004458846,0.0001938296],"domain_scores_gemma":[0.9991431,0.0001229235,0.00002807323,0.000469139,0.0001331926,0.0001036015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005917918,0.002387104,0.03401985,0.0003801135,0.0001410327,0.00008064476,0.2217484,0.01595307,0.0470293,0.634351,0.008634328,0.03468348],"study_design_scores_gemma":[0.005844234,0.002437152,0.2959796,0.0003708292,0.0001015867,0.0002777269,0.009570198,0.5106209,0.09358535,0.02650365,0.05365077,0.001057923],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8223384,0.00004407034,0.1487591,0.01566147,0.0008968475,0.0003526585,0.000006629471,0.0001306771,0.01181013],"genre_scores_gemma":[0.9869286,9.563803e-7,0.004130485,0.008721846,0.0001840701,0.00001324917,0.0000110264,0.000004165518,0.000005556522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6078473,"threshold_uncertainty_score":0.2708246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02257485962310858,"score_gpt":0.2425481105737075,"score_spread":0.2199732509505989,"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."}}