{"id":"W2171959510","doi":"10.1145/2213977.2214051","title":"Characterizing pseudoentropy and simplifying pseudorandom generator constructions","year":2012,"lang":"en","type":"article","venue":"","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Environment and Climate Change Canada; Microsoft Research; National Science Foundation","keywords":"Pseudorandom number generator; Random variable; Entropy (arrow of time); Discrete mathematics; Mathematics; Probabilistic logic; Polynomial; Combinatorics; Algorithm; Statistics; Physics; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001813731,0.0001003448,0.0001148545,0.00008136374,0.0002415387,0.0001995015,0.0002014486,0.00003779856,0.00004446094],"category_scores_gemma":[0.00001526157,0.0000862018,0.00004114426,0.0002181718,0.00006010306,0.001345535,0.0001881299,0.00008663379,0.00001998286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006768579,"about_ca_system_score_gemma":0.00001232434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000141839,"about_ca_topic_score_gemma":0.000001835875,"domain_scores_codex":[0.9992179,0.00003583911,0.0001417934,0.0001985202,0.0001036348,0.0003023285],"domain_scores_gemma":[0.9993858,0.00005162197,0.00004272916,0.0003030961,0.00002456677,0.00019215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000581112,0.00005266742,0.03281183,0.00001445577,0.00002149941,0.000001600458,0.0006802888,1.612548e-7,0.01720981,0.9341841,0.0006831583,0.01433466],"study_design_scores_gemma":[0.01331331,0.0003383601,0.2740977,0.0001301319,0.0002120568,0.003666905,0.00221976,0.03779105,0.1228508,0.05041517,0.4902428,0.004721879],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3760576,0.0004389494,0.6211753,0.0003948066,0.0005800146,0.0000945452,0.00001102171,0.0001949552,0.001052754],"genre_scores_gemma":[0.8855143,0.0000822008,0.1136305,0.0005579493,0.0001954582,0.000007452354,0.000004704702,0.000003951396,0.000003519942],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8837689,"threshold_uncertainty_score":0.3515207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509360197328167,"score_gpt":0.2371142638527784,"score_spread":0.2220206618794968,"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."}}