{"id":"W2962746473","doi":"10.1109/icc.2019.8761802","title":"Capacity-Achieving Private Information Retrieval Codes with Optimal Message Size and Upload Cost","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Upload; Computer science; Private information retrieval; Computer network; Computer security; World Wide Web","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":[0.002565071,0.0009929636,0.001251087,0.001188303,0.00116735,0.002311931,0.002586851,0.001832283,0.003110606],"category_scores_gemma":[0.01913259,0.0005045129,0.0007337857,0.002005186,0.002820543,0.004378914,0.003482304,0.002896238,0.001083545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002270268,"about_ca_system_score_gemma":0.003133047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001086432,"about_ca_topic_score_gemma":0.0007521571,"domain_scores_codex":[0.9966909,0.0009758785,0.000149049,0.000416058,0.001195975,0.0005721409],"domain_scores_gemma":[0.983497,0.009390941,0.001657655,0.002962474,0.001921957,0.0005699694],"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":[0.000496201,0.0001696692,0.0005484709,0.000298422,0.00003637029,0.0002392199,0.0002986045,0.1572196,0.02041939,0.773048,0.004849336,0.04237669],"study_design_scores_gemma":[0.0001277682,0.0002202173,0.0001946179,0.00005790891,0.00002968807,0.0004242284,0.00008123193,0.647314,0.01691396,0.3298267,0.004727932,0.0000816684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08107825,0.0006144404,0.8983657,0.00153892,0.00009608054,0.000252814,0.0004192957,0.0007597404,0.01687485],"genre_scores_gemma":[0.7999055,0.0007449001,0.1910837,0.0004873281,0.0002303502,0.0006969687,0.0004010598,0.000253465,0.006196509],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003110606,"threshold_uncertainty_score":0.01647204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01318077058428835,"score_gpt":0.223004622777262,"score_spread":0.2098238521929736,"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."}}