{"id":"W3194688402","doi":"","title":"Improved Garbled Circuit Building Blocks and Applications to Auctions and Computing Minima.","year":2009,"lang":"en","type":"preprint","venue":"IACR Cryptology ePrint Archive","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Computer science; Subtraction; Computation; Maxima and minima; Multiplication (music); Integer (computer science); Adder; Function (biology); Selection (genetic algorithm); Common value auction; Secure multi-party computation; Theoretical computer science; Algorithm; Arithmetic; Mathematics; Artificial intelligence; Programming language; Latency (audio)","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":[0.002898724,0.0008546969,0.001100235,0.001136642,0.0007663074,0.002317355,0.002045667,0.001435879,0.006724142],"category_scores_gemma":[0.006622962,0.0005999057,0.001338419,0.001334684,0.002147053,0.006172451,0.002785902,0.003266748,0.001049903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00133884,"about_ca_system_score_gemma":0.0007427563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001923768,"about_ca_topic_score_gemma":0.0003083213,"domain_scores_codex":[0.9977624,0.0009255154,0.0001409071,0.0002429438,0.0007256885,0.0002024194],"domain_scores_gemma":[0.9973826,0.001298281,0.0001835629,0.0008536561,0.0001932365,0.00008863748],"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":[0.0002088042,0.00007304463,0.0001872519,0.0001660195,0.00004138104,0.0001203368,0.0001320546,0.04690251,0.00907477,0.9102994,0.001127896,0.03166652],"study_design_scores_gemma":[0.0001123833,0.0002263854,0.0001317297,0.0001000143,0.00005611189,0.0002769006,0.00004525277,0.273614,0.02759905,0.6857955,0.01199327,0.00004926999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02122395,0.000605151,0.967091,0.0005452354,0.0001007247,0.0001736184,0.00009017793,0.0004724459,0.009697645],"genre_scores_gemma":[0.5414239,0.000766708,0.4481484,0.0004084051,0.0001213452,0.0003748783,0.0002036303,0.0002059432,0.008346666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006724142,"threshold_uncertainty_score":0.02249449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169894846260855,"score_gpt":0.2754775934787398,"score_spread":0.2584881088526543,"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."}}