{"id":"W2807633791","doi":"10.1109/tkde.2018.2857471","title":"Secure and Efficient Skyline Queries on Encrypted Data","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Institutes of Health; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Patient-Centered Outcomes Research Institute","keywords":"Computer science; Encryption; Cloud computing; Skyline; Scalability; Database; Outsourcing; Computer network; Data mining; Operating system","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":[0.0002694349,0.0001944149,0.0001571875,0.0002034296,0.0002340495,0.000152354,0.001067265,0.00007043251,0.00001367119],"category_scores_gemma":[0.00001754358,0.0001811466,0.00001594622,0.0004954873,0.00008907569,0.0006743341,0.00009002592,0.0002262428,0.00002620367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009107695,"about_ca_system_score_gemma":0.00002923531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001616767,"about_ca_topic_score_gemma":0.0000831423,"domain_scores_codex":[0.9987118,0.00002260998,0.0001735018,0.0007312957,0.0001274973,0.0002333467],"domain_scores_gemma":[0.9975647,0.0001429492,0.00002404711,0.002077244,0.00005100508,0.0001400144],"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":[0.0003695,0.003172555,0.00007025102,0.0009447517,0.0006581213,0.00008471085,0.01237388,0.00703934,0.01000794,0.1217287,0.02039197,0.8231583],"study_design_scores_gemma":[0.0004913128,0.0002286566,0.0002789197,0.0001128487,0.00003219968,0.00002875751,0.00003432758,0.936373,0.003111998,0.00006824882,0.05889122,0.0003485423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01080296,0.0006507462,0.9861723,0.00009742921,0.0007115857,0.0001134361,0.001074229,0.0002199408,0.00015735],"genre_scores_gemma":[0.9782171,0.0003216967,0.02109076,0.00005316688,0.0001323453,0.000006455839,0.0001564057,0.0000145897,0.000007526477],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9674141,"threshold_uncertainty_score":0.7386945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02885223219186742,"score_gpt":0.2747359068435998,"score_spread":0.2458836746517324,"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."}}