{"id":"W3082420143","doi":"","title":"Secure Multi-party Computation of Differentially Private Median","year":2020,"lang":"en","type":"article","venue":"USENIX Security Symposium","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Computation; Computer security; Secure multi-party computation; Cryptography; Algorithm","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"],"consensus_categories":[],"category_scores_codex":[0.0001845591,0.0002814017,0.0003993452,0.0001293082,0.0001292708,0.0001517142,0.001161039,0.0001584955,0.00002133125],"category_scores_gemma":[0.00005537524,0.0002765843,0.0002158265,0.0007607941,0.0001283269,0.0007305974,0.0005721173,0.0003231588,0.00003590269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001735052,"about_ca_system_score_gemma":0.00006693212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005551962,"about_ca_topic_score_gemma":0.00007863991,"domain_scores_codex":[0.9977393,0.0001713378,0.0005241664,0.0006639167,0.0005138473,0.0003874773],"domain_scores_gemma":[0.998572,0.00008536442,0.0002662433,0.0005632701,0.0001479382,0.0003652206],"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":[0.0002866914,0.00263351,0.02045737,0.001672093,0.0004936032,0.000220381,0.1478218,0.0005377085,0.1516619,0.6590694,0.009034636,0.006110962],"study_design_scores_gemma":[0.006886771,0.001132341,0.01363615,0.0002262953,0.0001722043,0.00005738844,0.0003910483,0.7954959,0.1084424,0.04770536,0.02361784,0.002236217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.267513,0.0001409778,0.724474,0.00599473,0.0005968728,0.0004466175,0.000163821,0.0004219453,0.000248068],"genre_scores_gemma":[0.9689417,0.00005053237,0.03021323,0.0005380758,0.0001415326,0.000008139115,0.00008936463,0.00001638068,9.652442e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7949582,"threshold_uncertainty_score":0.9999686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01843401474372736,"score_gpt":0.2405021136164807,"score_spread":0.2220680988727534,"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."}}