{"id":"W2396392723","doi":"","title":"One (Block) Size Fits All: PIR and SPIR with Variable-Length Records via Multi-Block Queries.","year":2013,"lang":"en","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Robustness (evolution); Block (permutation group theory); Block size; Decoding methods; Theoretical computer science; Algorithm; Mathematics; 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":[0.006294201,0.0007735076,0.001707872,0.001054792,0.001715201,0.002634271,0.004464661,0.002852286,0.005885274],"category_scores_gemma":[0.02044416,0.0008725222,0.001344387,0.002168771,0.003695273,0.01327684,0.01158439,0.003622383,0.003171588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001439805,"about_ca_system_score_gemma":0.002868401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007886599,"about_ca_topic_score_gemma":0.0005542685,"domain_scores_codex":[0.9920537,0.002928453,0.0005851071,0.001144468,0.002413727,0.0008744032],"domain_scores_gemma":[0.977191,0.005896394,0.002067203,0.01280128,0.001435425,0.000608763],"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":[0.001888645,0.0003992494,0.003185124,0.000706176,0.0002638548,0.0009052722,0.002408338,0.04152606,0.0576909,0.6803433,0.01226999,0.198413],"study_design_scores_gemma":[0.0004004667,0.001317028,0.001605853,0.0001567572,0.0002387802,0.002059379,0.001200052,0.3968546,0.1034428,0.4389281,0.05339155,0.0004047008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04035215,0.0005979649,0.9430732,0.001368263,0.0001179843,0.0005721342,0.0007631999,0.002162032,0.01099305],"genre_scores_gemma":[0.6045529,0.0004545198,0.3799966,0.0009089066,0.0002042044,0.0009101062,0.00114191,0.0004815506,0.01134939],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006294201,"threshold_uncertainty_score":0.03328735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01454455593149966,"score_gpt":0.2131671917103611,"score_spread":0.1986226357788614,"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."}}