{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00398935,0.000921621,0.001807951,0.001129407,0.001500519,0.00224912,0.001693395,0.001588016,0.001913668],"category_scores_gemma":[0.00931586,0.0004944067,0.001067049,0.002173307,0.001295654,0.003416653,0.002188189,0.001812719,0.0003110355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002463802,"about_ca_system_score_gemma":0.002906379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002136022,"about_ca_topic_score_gemma":0.002531409,"domain_scores_codex":[0.9954008,0.001822689,0.0001943697,0.0006730161,0.001380687,0.0005283597],"domain_scores_gemma":[0.9960803,0.002484387,0.0003672748,0.0004419402,0.0003627654,0.0002632802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006796491,0.0003708017,0.00352365,0.0003285904,0.0002003521,0.000391917,0.0004696504,0.6990419,0.01002984,0.09091128,0.003000557,0.1910518],"study_design_scores_gemma":[0.00003531929,0.00006747665,0.000330048,0.00001184029,0.00002593124,0.0001913245,0.00009141655,0.9573443,0.00210919,0.03871883,0.001058302,0.00001602582],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04359724,0.0004820118,0.952868,0.0006487502,0.00003170937,0.0001596801,0.00004407132,0.0001872309,0.001981243],"genre_scores_gemma":[0.7789862,0.0004004574,0.2183894,0.0001654094,0.00007167758,0.0001271697,0.00009098276,0.0000674562,0.00170128],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00398935,"threshold_uncertainty_score":0.02109796,"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."}}