{"id":"W4290994019","doi":"10.1109/icc45855.2022.9839017","title":"Achieving Privacy-Preserving Weighted Similarity Range Query over Outsourced eHealthcare Data","year":2022,"lang":"en","type":"article","venue":"ICC 2022 - IEEE International Conference on Communications","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Range query (database); Encryption; Information retrieval; Data mining; Cloud computing; Similarity (geometry); Query optimization; Nearest neighbor search; Homomorphic encryption; Leverage (statistics); Information privacy; Web search query; Web query classification; Outsourcing; Theoretical computer science; Search engine; Artificial intelligence; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003423015,0.0007207876,0.001749712,0.0009553368,0.001031877,0.001937409,0.001857336,0.001269618,0.001790318],"category_scores_gemma":[0.01047414,0.0003213226,0.001161186,0.002531999,0.001052881,0.006787797,0.005088477,0.001528698,0.0006791386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009970499,"about_ca_system_score_gemma":0.001623446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001465167,"about_ca_topic_score_gemma":0.0007280431,"domain_scores_codex":[0.99243,0.001634928,0.0007803356,0.001074632,0.003204912,0.0008751429],"domain_scores_gemma":[0.9937831,0.001842578,0.0006553127,0.002439023,0.001077781,0.0002021641],"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":[0.00232658,0.0005207307,0.007665345,0.001097547,0.0004018196,0.002264408,0.002487539,0.1858127,0.1011184,0.2394928,0.0142987,0.4425135],"study_design_scores_gemma":[0.0002129172,0.0005084921,0.001454567,0.00004623209,0.0001065677,0.002064476,0.0008880841,0.835434,0.05057416,0.09782577,0.01076915,0.000115536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0712661,0.0008831095,0.9209465,0.0008123852,0.00008230234,0.0003426005,0.0005597434,0.0008063188,0.004300826],"genre_scores_gemma":[0.8997813,0.0006307074,0.09532422,0.0003871075,0.0001190694,0.0002229555,0.0007677971,0.00006017087,0.002706628],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003423015,"threshold_uncertainty_score":0.01810288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2082270553343684,"score_gpt":0.3896952466490169,"score_spread":0.1814681913146485,"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."}}