{"id":"W2739564306","doi":"10.1109/icc.2017.7997105","title":"CryptMDB: A practical encrypted MongoDB over big data","year":2017,"lang":"en","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Homomorphic encryption; Encryption; Cryptosystem; NoSQL; Relational database; Big data; Database; Confidentiality; Relational database management system; Computer security; Data access; Scalability; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004470657,0.0001399972,0.0001476322,0.00007549766,0.0005201786,0.001297157,0.004707587,0.00008298988,0.0001252616],"category_scores_gemma":[0.0005861819,0.0001151692,0.00005492581,0.0001346114,0.0001453251,0.003396047,0.004267189,0.0002078317,0.0001681509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007311735,"about_ca_system_score_gemma":0.00009438511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003998251,"about_ca_topic_score_gemma":0.0002470488,"domain_scores_codex":[0.9984178,0.00004555231,0.0001827698,0.0006873652,0.0003492805,0.0003172569],"domain_scores_gemma":[0.9925223,0.0001377867,0.0001338718,0.006976972,0.0000523467,0.0001767454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001248481,0.0001948045,0.003452669,0.000007042301,0.00003049506,0.00007737341,0.0001038803,1.038063e-7,0.0002023777,0.8467812,0.09677447,0.0523631],"study_design_scores_gemma":[0.001318521,0.0001141831,0.1269618,0.00002539307,0.00003110333,0.00008945744,0.00003170481,0.05603183,0.0008532022,0.08354882,0.7302476,0.0007463794],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007149315,0.0000465276,0.9496955,0.00439416,0.0009926037,0.0001461532,0.00006938401,0.0002895881,0.03721679],"genre_scores_gemma":[0.732844,0.00006658855,0.2653856,0.001089384,0.0004578324,0.00000770317,0.00006022143,0.00001079201,0.00007789127],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7632324,"threshold_uncertainty_score":0.9997396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1600290286578373,"score_gpt":0.3641026951482287,"score_spread":0.2040736664903915,"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."}}