{"id":"W7154594284","doi":"10.1109/iceteg66194.2025.11473203","title":"Encrypted Vector Operations for Privacy-Preserving Machine Learning and Data Retrieval","year":2025,"lang":"","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Data retrieval; Support vector machine; Encryption; Key (lock); Pattern recognition (psychology); Relevance (law)","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":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.001343721,0.0003065389,0.0003532907,0.0003025685,0.001366897,0.001558137,0.00364607,0.0001639276,0.0002566785],"category_scores_gemma":[0.002821299,0.0003026472,0.00008493588,0.001516311,0.000150454,0.002208276,0.009986855,0.0004851237,0.000005653456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002407475,"about_ca_system_score_gemma":0.0003022808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003815281,"about_ca_topic_score_gemma":0.0004727161,"domain_scores_codex":[0.997005,0.000213955,0.0005629376,0.001424873,0.0002783358,0.0005148856],"domain_scores_gemma":[0.9962806,0.000704834,0.00008018807,0.002516443,0.0002355309,0.0001824192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003682465,0.0005264251,0.008906631,0.0007494417,0.0004642294,0.000009709362,0.002753165,0.0001561482,0.005506201,0.9190543,0.01547659,0.04602886],"study_design_scores_gemma":[0.001008943,0.0001457743,0.001655027,0.0001089815,0.00008255219,0.000004176663,0.0001036503,0.9025183,0.000672679,0.003618724,0.08976765,0.0003135941],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007795851,0.004957112,0.9780544,0.005479087,0.0007757674,0.0008853055,0.0006608091,0.0001798554,0.001211809],"genre_scores_gemma":[0.6808097,0.001716391,0.3145292,0.0006737552,0.0002118477,0.00001957647,0.001189945,0.0000222073,0.0008273892],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9154356,"threshold_uncertainty_score":0.9999425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0374423243990644,"score_gpt":0.3252879695289174,"score_spread":0.287845645129853,"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."}}