{"id":"W34785529","doi":"","title":"Outsourcing Multi-Party Computation.","year":2011,"lang":"en","type":"preprint","venue":"IACR Cryptology ePrint Archive","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Protocol (science); Secure two-party computation; Outsourcing; Computation; Set (abstract data type); Construct (python library); Secure multi-party computation; Standard Model (mathematical formulation); Scheme (mathematics); Computer security; Programming language; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004303315,0.001013672,0.001395362,0.0007227086,0.00154357,0.003634978,0.002687411,0.001928841,0.01146801],"category_scores_gemma":[0.008896807,0.0007453567,0.001844872,0.001923465,0.003733004,0.007441579,0.007507343,0.004452041,0.002813668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002480262,"about_ca_system_score_gemma":0.002555924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007997425,"about_ca_topic_score_gemma":0.0008491183,"domain_scores_codex":[0.9928353,0.002552562,0.0004396529,0.001142191,0.002349052,0.0006811735],"domain_scores_gemma":[0.9908194,0.002661511,0.000498901,0.00522388,0.0004355694,0.0003606597],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006130982,0.00004791079,0.0003085562,0.0002922555,0.00004139886,0.0001716529,0.0002131391,0.01314001,0.001631191,0.9584835,0.002925335,0.02268388],"study_design_scores_gemma":[0.00003172419,0.00006118766,0.0001836193,0.0001016134,0.00003584709,0.0003921509,0.00009538716,0.122262,0.004338286,0.8295241,0.04294891,0.00002512344],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009805077,0.002123821,0.9358369,0.002941051,0.0003652565,0.0004001818,0.000357171,0.0005515987,0.04761893],"genre_scores_gemma":[0.6427596,0.00448968,0.3124824,0.001143689,0.000582651,0.0007098781,0.0007326126,0.0002332093,0.0368663],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01146801,"threshold_uncertainty_score":0.03836435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04780136964815156,"score_gpt":0.2858845172483337,"score_spread":0.2380831476001821,"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."}}