{"id":"W2592025126","doi":"10.1109/tc.2017.2676763","title":"Efficient Composited de Bruijn Sequence Generators","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Computers","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Standards and Technology; Cisco Systems","keywords":"De Bruijn sequence; Sequence (biology); Computer science; Application-specific integrated circuit; Algorithm; Stream cipher; Parallel computing; Discrete mathematics; Mathematics; Cryptography; Computer hardware","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":[],"consensus_categories":[],"category_scores_codex":[0.0002507725,0.0001850532,0.0001553547,0.0002632007,0.00126254,0.0005159272,0.001577355,0.00005394803,0.00001140655],"category_scores_gemma":[0.000001883547,0.0001888928,0.0001762843,0.0002677734,0.0001584871,0.0001710616,0.00001015354,0.0002326824,0.00005168462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007438815,"about_ca_system_score_gemma":0.00005556217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003970047,"about_ca_topic_score_gemma":0.00001625143,"domain_scores_codex":[0.9987431,0.00009985438,0.0001724454,0.000420816,0.0002191261,0.0003447089],"domain_scores_gemma":[0.9984071,0.0001125212,0.00009894265,0.001157328,0.00004955269,0.0001745689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005806145,0.0005139946,0.0001439757,0.00001919061,0.0001372277,0.0001055966,0.001137866,0.7189659,0.01280505,0.03362972,0.0006380947,0.2318452],"study_design_scores_gemma":[0.0005683348,0.0001591323,0.0006054337,0.0000748307,0.00001919242,0.00004805109,0.000006349508,0.9490164,0.04740735,0.001046711,0.0006665484,0.0003816807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1190168,0.000008360625,0.8778011,0.0005366704,0.00177595,0.0001068057,0.00000576882,0.0003052302,0.0004433211],"genre_scores_gemma":[0.94885,0.000003550766,0.05043822,0.0005939325,0.0000493453,0.00001257257,3.271316e-7,0.00001069849,0.00004130439],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8298333,"threshold_uncertainty_score":0.9710566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02651520188252763,"score_gpt":0.2631694293226665,"score_spread":0.2366542274401388,"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."}}