{"id":"W2321314104","doi":"10.1109/tsc.2015.2426185","title":"Trust and Reputation of Web Services Through QoS Correlation Lens","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Services Computing","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Reputation; Quality of service; Web service; Service (business); Service provider; WS-Policy; Selection (genetic algorithm); Mobile QoS; World Wide Web; Data mining; Computer network; Web application security; Machine learning; Web development","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003113655,0.0005984514,0.000856955,0.001867087,0.0009677011,0.003446282,0.0008429466,0.0009671513,0.001155125],"category_scores_gemma":[0.01952219,0.0005044977,0.0006568747,0.001668488,0.001654713,0.005863226,0.001657286,0.001672523,0.0003328165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002793796,"about_ca_system_score_gemma":0.001749829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006053383,"about_ca_topic_score_gemma":0.004295022,"domain_scores_codex":[0.9965106,0.001395583,0.0001706358,0.0004684997,0.001199133,0.0002556241],"domain_scores_gemma":[0.989218,0.005296636,0.002058258,0.001252261,0.001706037,0.0004688404],"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":[0.0005220943,0.000203842,0.01599688,0.0001754112,0.0001951369,0.0006391833,0.001130457,0.4012942,0.009002169,0.3902379,0.003689098,0.1769136],"study_design_scores_gemma":[0.00001124676,0.00002878894,0.001413048,0.00001256837,0.00002717052,0.0001134923,0.00007467695,0.9508722,0.001898186,0.04423496,0.001282996,0.00003057187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1272245,0.0009778375,0.8587227,0.001385273,0.00007302946,0.00007435998,0.00008692925,0.0006920693,0.01076321],"genre_scores_gemma":[0.9636607,0.0001889339,0.03455524,0.00004258287,0.00004204176,0.00002115898,0.00003317765,0.00003610265,0.00142007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006053383,"threshold_uncertainty_score":0.02027047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01835333284390641,"score_gpt":0.2458715172939186,"score_spread":0.2275181844500122,"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."}}