{"id":"W2133597905","doi":"10.1109/cit.2012.208","title":"An Efficient Hardware Random Number Generator Based on the MT Method","year":2012,"lang":"en","type":"article","venue":"","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Field-programmable gate array; Computer hardware; Throughput; Embedded system; Key (lock); Generator (circuit theory); Random number generation; Software; Parallel computing; Operating system; Power (physics); Algorithm","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":[0.0003400231,0.0003678319,0.0003787475,0.000519444,0.0002413087,0.0002678549,0.0005400814,0.0003091584,0.002806589],"category_scores_gemma":[0.001432569,0.0001646607,0.0002073371,0.0004819586,0.0002556874,0.0005108867,0.0003407019,0.000344371,0.0008058973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002497249,"about_ca_system_score_gemma":0.0003452443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000253322,"about_ca_topic_score_gemma":0.0003632265,"domain_scores_codex":[0.9995269,0.0001559173,0.00002907795,0.00006707689,0.0001798885,0.00004117904],"domain_scores_gemma":[0.9994949,0.0001929824,0.00006998563,0.00009942962,0.0001194652,0.00002319361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008237977,0.0001125738,0.001755255,0.0003531719,0.00006642197,0.0006147216,0.0001353518,0.1218171,0.2140458,0.05632522,0.008397833,0.5955527],"study_design_scores_gemma":[0.0002256543,0.0006193219,0.001066917,0.00002742592,0.00003412707,0.001240353,0.00001334592,0.8850582,0.08638772,0.008264634,0.01700938,0.00005298786],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03011255,0.0002398671,0.9632657,0.0001296386,0.00009064718,0.0001719986,0.0001136553,0.002471326,0.003404569],"genre_scores_gemma":[0.5338113,0.0001550304,0.459977,0.0001284128,0.00008013967,0.0003132673,0.0002820407,0.0001306277,0.005122183],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002806589,"threshold_uncertainty_score":0.009388924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02095360985761418,"score_gpt":0.2920302674127464,"score_spread":0.2710766575551322,"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."}}