{"id":"W4241698118","doi":"10.32920/ryerson.14655171","title":"End-to-end QoS computation for vertical service composition in the cloud","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cloud computing; Quality of service; Mobile QoS; Computer science; Service (business); Software as a service; Service provider; Scalability; Cloud testing; Service catalog; Data as a service; Computer network; Service design; Software; Cloud computing security; Database; Business; Software development; Operating system","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":[0.001517519,0.0009591199,0.0007556551,0.0008454041,0.001360102,0.002008746,0.001240407,0.0007300131,0.002378739],"category_scores_gemma":[0.003572938,0.0003942036,0.0007098345,0.0007987421,0.0005637127,0.001748846,0.001719639,0.001561515,0.0006529652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002317648,"about_ca_system_score_gemma":0.002599245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01055999,"about_ca_topic_score_gemma":0.00947276,"domain_scores_codex":[0.9986761,0.0002101088,0.00009505089,0.0002530493,0.0005393624,0.0002264022],"domain_scores_gemma":[0.9988367,0.0003509677,0.0001166549,0.0001732048,0.0003971406,0.00012532],"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":[0.0005780621,0.000368032,0.00594426,0.0001789012,0.00008590896,0.0003611653,0.0004361419,0.6535224,0.03640596,0.08035914,0.005127352,0.2166326],"study_design_scores_gemma":[0.000004174349,0.00001410203,0.0001383792,0.000004633879,0.000003989966,0.00001199032,0.00002517181,0.9925385,0.002276751,0.004430427,0.000547056,0.000004779164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02525755,0.00009799434,0.9712166,0.0001911929,0.00004415257,0.0001177024,0.00007026165,0.0008044932,0.002200088],"genre_scores_gemma":[0.5607017,0.000169672,0.4362893,0.00008780351,0.00004470022,0.0001539137,0.0004215632,0.0001146151,0.002016819],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01055999,"threshold_uncertainty_score":0.02099705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02080708620877957,"score_gpt":0.2791565207052727,"score_spread":0.2583494344964931,"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."}}