{"id":"W4280510104","doi":"10.3390/math10101675","title":"Balancing Privacy Risk and Benefit in Service Selection for Multiprovision Cloud Service Composition","year":2022,"lang":"en","type":"article","venue":"Mathematics","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nipissing University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cloud computing; Popularity; Computer science; Service (business); Service provider; Computer security; Selection (genetic algorithm); Internet privacy; Business; Artificial intelligence","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0007949924,0.0001456752,0.000193508,0.0001683441,0.0004870855,0.0001469554,0.005284941,0.00007267664,0.000005008372],"category_scores_gemma":[0.001127307,0.0001569091,0.00002351997,0.0008711242,0.00001164615,0.0003879343,0.0254914,0.0003109323,0.00000502071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002253889,"about_ca_system_score_gemma":0.00002620141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002756859,"about_ca_topic_score_gemma":0.0003517419,"domain_scores_codex":[0.9986802,0.00004215799,0.0003180467,0.0004000053,0.0002948342,0.0002647651],"domain_scores_gemma":[0.9973323,0.0003475756,0.0002282052,0.001958218,0.0001004854,0.00003323051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000524052,0.00782988,0.07859228,0.01554016,0.0004477015,0.00006606649,0.07758255,0.05771925,0.1134901,0.2824024,0.06388055,0.301925],"study_design_scores_gemma":[0.0004176762,0.00005550147,0.000558786,0.00004183176,0.000007201923,0.00002404545,0.0001116104,0.736226,0.001299859,0.2607791,0.0003446916,0.0001336393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5352165,0.00004268437,0.4571645,0.006305042,0.0001694629,0.0005934677,0.00003700053,0.0004376303,0.00003380995],"genre_scores_gemma":[0.3453969,0.00000942011,0.6541057,0.0002911887,0.00002119838,0.0001291482,0.00002357701,0.00001625356,0.000006686446],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6785068,"threshold_uncertainty_score":0.9823902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02172882568743561,"score_gpt":0.2617903060912465,"score_spread":0.2400614804038109,"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."}}