{"id":"W2612444462","doi":"10.23919/date.2017.7927058","title":"A true random number generator based on parallel STT-MTJs","year":2017,"lang":"en","type":"article","venue":"","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Random number generation; NIST; Computer science; Pseudorandom number generator; Randomness; Cryptography; Spin-transfer torque; Encryption; Cryptographic protocol; Randomness tests; Monte Carlo method; CMOS; Electronic engineering; Algorithm; Engineering; Mathematics; Computer network; Physics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003959575,0.0001909981,0.0002054056,0.00005901325,0.0004027511,0.0006630687,0.00124581,0.00006778819,0.0004805594],"category_scores_gemma":[0.0001431894,0.0001558774,0.000125491,0.00008153963,0.00006360122,0.0006995196,0.0001523615,0.0001429995,0.001280731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006115686,"about_ca_system_score_gemma":0.0001260106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001338824,"about_ca_topic_score_gemma":0.00002866251,"domain_scores_codex":[0.9984933,0.00009152357,0.000208598,0.0004869046,0.0004112709,0.0003084582],"domain_scores_gemma":[0.9978988,0.0001345663,0.0001391168,0.001582154,0.00008770912,0.0001576361],"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":[0.002753863,0.002651204,0.01169615,0.0001647312,0.0002237601,0.0009993779,0.001124126,0.05356797,0.1189492,0.3370437,0.265644,0.2051818],"study_design_scores_gemma":[0.006117318,0.000108573,0.003233123,0.00002627444,0.000007866584,0.000006600232,0.000003079915,0.9677178,0.01360527,0.001864227,0.006949259,0.0003606654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01962007,0.000007057535,0.9459376,0.003139134,0.0005148971,0.000248587,0.000002929005,0.0002442137,0.03028547],"genre_scores_gemma":[0.8862967,0.000002852101,0.1082837,0.002949887,0.0002174594,0.00004253342,0.000003826435,0.00001629956,0.002186629],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9141498,"threshold_uncertainty_score":0.9994969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02006333025685998,"score_gpt":0.2716360116350677,"score_spread":0.2515726813782077,"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."}}