{"id":"W4389010994","doi":"10.1007/978-3-031-48615-9_10","title":"Public-Key Encryption, Local Pseudorandom Generators, and the Low-Degree Method","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Università Bocconi; Chinese University of Hong Kong; European Commission; National Science Foundation","keywords":"Computer science; Degree (music); Encryption; Pseudorandom number generator; Public-key cryptography; Theoretical computer science; Key (lock); Cryptography; Pseudorandom function family; Scheme (mathematics); Context (archaeology); Symmetric-key algorithm; Generator (circuit theory); Algorithm; Computer security; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003971239,0.0005983103,0.0007021552,0.0008946258,0.0006594232,0.001584903,0.004143138,0.0003805403,0.00001587427],"category_scores_gemma":[0.0002423593,0.0004146031,0.0002253826,0.001487693,0.002585321,0.0009492012,0.002737426,0.001094657,0.00004139449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009523344,"about_ca_system_score_gemma":0.0004721411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007141721,"about_ca_topic_score_gemma":0.0002933829,"domain_scores_codex":[0.9953504,0.0002077658,0.0006227761,0.001840505,0.00120939,0.0007691366],"domain_scores_gemma":[0.9953876,0.001761426,0.0002877838,0.001965532,0.0003282668,0.0002694597],"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":[0.00001722386,0.00001333558,0.00001386255,0.00003081343,0.00001891029,0.000037477,0.0006936683,0.0008364632,0.00001352366,0.5535709,0.0001197474,0.4446341],"study_design_scores_gemma":[0.001241522,0.00006023322,0.00007693387,0.000126803,0.00001424363,0.00009749336,5.264765e-7,0.3158546,0.0001768529,0.6788359,0.002952963,0.0005618712],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002053278,0.001078096,0.9919444,0.003254409,0.00186482,0.0005040811,0.00002359092,0.0002862609,0.001023822],"genre_scores_gemma":[0.0287755,0.0007726167,0.9652511,0.003941658,0.001054019,0.00004502877,0.00002883566,0.00006448356,0.00006677864],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4440722,"threshold_uncertainty_score":0.9998306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03330693155059561,"score_gpt":0.253333217140938,"score_spread":0.2200262855903424,"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."}}