{"id":"W2975679388","doi":"10.1109/isit.2019.8849528","title":"Private Information Retrieval from Locally Repairable Databases with Colluding Servers","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Server; Code (set theory); Dimension (graph theory); Code rate; Field size; Private information retrieval; Computer science; Discrete mathematics; Locality; Combinatorics; Algorithm; Database; Theoretical computer science; Physics; Mathematics; Computer network; Decoding methods; Set (abstract data type); Computer security","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":[0.002246,0.0009196079,0.001793437,0.001040331,0.001136101,0.002847431,0.002256379,0.001811824,0.001938989],"category_scores_gemma":[0.01276784,0.0005263268,0.0008232252,0.002867141,0.002268462,0.004355473,0.003370817,0.001277476,0.0007350115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001870765,"about_ca_system_score_gemma":0.001136558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001572839,"about_ca_topic_score_gemma":0.0006893228,"domain_scores_codex":[0.9971074,0.0009997768,0.000147604,0.0004190822,0.000852434,0.0004737104],"domain_scores_gemma":[0.9916285,0.005094841,0.0009088284,0.001403982,0.0006844448,0.0002794628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00178208,0.0001688546,0.002048457,0.0005852213,0.0001509397,0.002145982,0.0008694843,0.6448268,0.01648037,0.2789547,0.003255711,0.04873144],"study_design_scores_gemma":[0.00006758398,0.000141527,0.0001992393,0.00002680325,0.00004060024,0.0004826019,0.000224163,0.937428,0.004425459,0.05593483,0.0009973291,0.0000319196],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2804529,0.00199812,0.7070766,0.001135155,0.00006542595,0.0001613669,0.0002844706,0.0003159847,0.008509886],"genre_scores_gemma":[0.9648603,0.0007538502,0.02913644,0.00009081153,0.0001106236,0.0001134921,0.0001667701,0.00003806069,0.004729594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002847431,"threshold_uncertainty_score":0.01357341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509435698918285,"score_gpt":0.2270212789978661,"score_spread":0.2119269220086833,"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."}}