{"id":"W4402067451","doi":"10.18280/ijsse.140409","title":"Lightweight Pseudo Random Number Generator for Embedded Systems","year":2024,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pseudorandom number generator; Computer science; Encryption; Algorithm; Initialization; Cryptography; Randomness; Randomness tests; Embedded system; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000777781,0.0001135135,0.0001733986,0.000163361,0.00002955691,0.0004036257,0.0003517,0.00004748775,0.000009297531],"category_scores_gemma":[0.00009117336,0.00009866397,0.0001223441,0.0001007823,0.00001011198,0.0008889586,0.00005851036,0.0001932189,0.000005123293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009379279,"about_ca_system_score_gemma":0.00007229912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003908462,"about_ca_topic_score_gemma":5.281082e-7,"domain_scores_codex":[0.9989739,0.00002946858,0.0003952951,0.0001446282,0.0003374929,0.0001191926],"domain_scores_gemma":[0.9991494,0.0003272561,0.00008695075,0.00007522699,0.000276902,0.00008419346],"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":[0.0005295471,0.000114461,0.00004283062,0.0004499412,0.0009681435,0.000593641,0.005053071,0.1042375,0.03528285,0.839404,0.003000671,0.01032334],"study_design_scores_gemma":[0.001046467,0.00003870343,0.0000304819,0.0003288956,0.00001544049,0.0008400119,0.00001559335,0.9544035,0.002113556,0.001414057,0.03961775,0.0001355936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01134755,0.001542817,0.9815101,0.001475788,0.003838587,0.00009142514,0.00001737497,0.00006250307,0.0001138336],"genre_scores_gemma":[0.981558,0.0004150498,0.01690173,0.00009543551,0.0009607332,0.000005166561,0.000004649421,0.00001415564,0.00004513165],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9702104,"threshold_uncertainty_score":0.40234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005704587572250969,"score_gpt":0.2342380749776176,"score_spread":0.2285334874053666,"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."}}