{"id":"W4402811381","doi":"10.1109/iccc62479.2024.10681868","title":"An Efficient Privacy-preserving Logistic Regression Scheme for Aging-in-place Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research and Productivity Council; University of New Brunswick","funders":"National Research Council","keywords":"Logistic regression; Computer science; Scheme (mathematics); Information privacy; Computer security; Machine learning; Mathematics","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":[0.003747765,0.0008559687,0.001285727,0.0007884901,0.001284711,0.001664058,0.002171603,0.001077335,0.002043579],"category_scores_gemma":[0.01110166,0.0003228228,0.001079498,0.00125563,0.0009960847,0.003385604,0.004209961,0.001924819,0.001000192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001176086,"about_ca_system_score_gemma":0.001913089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001248502,"about_ca_topic_score_gemma":0.0008687194,"domain_scores_codex":[0.9952365,0.001778663,0.0003916723,0.0008151451,0.00113325,0.0006448857],"domain_scores_gemma":[0.9948612,0.0018042,0.0006963033,0.00163819,0.0008055251,0.0001945619],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003050136,0.0005312692,0.006697161,0.0005454115,0.0004997861,0.001710138,0.001260011,0.37852,0.05798895,0.1757305,0.0119058,0.3615609],"study_design_scores_gemma":[0.00008373503,0.0003402981,0.0005897488,0.00002780669,0.00006829348,0.000583917,0.0001203847,0.9549838,0.0107271,0.0274219,0.004977729,0.00007534295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03579787,0.0005252438,0.9598857,0.0007248868,0.0001298061,0.0001794673,0.0003244208,0.0007413923,0.001691243],"genre_scores_gemma":[0.9106097,0.0004206422,0.08449306,0.0002285564,0.0001181409,0.000168158,0.0003662016,0.00003898454,0.00355653],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003747765,"threshold_uncertainty_score":0.01982027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06277697137704924,"score_gpt":0.3790996406171492,"score_spread":0.3163226692401,"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."}}