{"id":"W2951443613","doi":"","title":"Succinct Randomized Encodings and their Applications.","year":2014,"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":"University of Toronto","funders":"","keywords":"Functional encryption; Plaintext; Obfuscation; Bounded function; Computer science; Cryptography; Theoretical computer science; Encoding (memory); ENCODE; Encryption; Secure multi-party computation; Simple (philosophy); Complexity class; Function (biology); Computation; Time complexity; Mathematics; Algorithm; Ciphertext","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":[0.005990307,0.001668067,0.001356804,0.001721398,0.001438339,0.004554838,0.002829673,0.002894021,0.008147755],"category_scores_gemma":[0.03166199,0.001334726,0.002462586,0.002891358,0.00516272,0.01379169,0.005570263,0.009010149,0.002238224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00429229,"about_ca_system_score_gemma":0.002829782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001062147,"about_ca_topic_score_gemma":0.0008743668,"domain_scores_codex":[0.9895857,0.003792044,0.0008945951,0.001784679,0.003165083,0.0007779492],"domain_scores_gemma":[0.9716378,0.01802735,0.001786244,0.007058797,0.001069478,0.000420373],"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":[0.0001572502,0.0000700981,0.0002222923,0.0002162805,0.00002700997,0.0001089929,0.0001773508,0.0203146,0.001596441,0.9494808,0.002541161,0.02508774],"study_design_scores_gemma":[0.00006379966,0.00005770474,0.00006569125,0.0001376568,0.00003062055,0.0001827751,0.00004147447,0.07443985,0.003962218,0.9088619,0.01211467,0.00004158529],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00811909,0.002187397,0.9704129,0.002404246,0.0003631055,0.0003187969,0.0008201554,0.001660613,0.01371365],"genre_scores_gemma":[0.3475576,0.004669272,0.6225622,0.002375824,0.0009561423,0.002160503,0.002845934,0.001073432,0.01579911],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008147755,"threshold_uncertainty_score":0.03168017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007846166356152841,"score_gpt":0.2319302358027464,"score_spread":0.2240840694465936,"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."}}