{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00178061,0.0001693006,0.0001432659,0.00005494666,0.0001916628,0.0001910465,0.0006928593,0.00004963243,0.0007864235],"category_scores_gemma":[0.00008883989,0.0001016126,0.0001006232,0.0003353301,0.00002898502,0.0003229303,0.00007249017,0.0001496542,0.0007297128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007154234,"about_ca_system_score_gemma":0.00006481152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003702439,"about_ca_topic_score_gemma":0.000002118967,"domain_scores_codex":[0.9980851,0.0005537649,0.0001816544,0.0003280077,0.0004761796,0.0003753125],"domain_scores_gemma":[0.9982368,0.0005061998,0.00006253777,0.0009091927,0.00009128419,0.0001939211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006042565,0.00354549,0.002607816,0.00005537491,0.00009440017,0.0000340988,0.003834401,0.2378654,0.1971006,0.4016934,0.06215889,0.09040593],"study_design_scores_gemma":[0.0008474529,0.00004489766,0.0005109101,0.000007096624,0.000007045075,0.000005193672,0.00001778332,0.9343609,0.06026098,0.00009398957,0.003674592,0.0001692025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01436424,0.00001513342,0.9782983,0.001601783,0.0004738612,0.000269871,0.000002894002,0.0002373089,0.00473658],"genre_scores_gemma":[0.7434859,3.468311e-7,0.2509317,0.005074795,0.0002439139,0.00004147636,0.00000379718,0.00001385477,0.0002042341],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7291216,"threshold_uncertainty_score":0.9379226,"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."}}