{"id":"W7098146709","doi":"","title":"Efficient jump ahead for F2-linear random number generators","year":2006,"lang":"en","type":"article","venue":"","topic":"Chaos-based Image/Signal Encryption","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Jump; Random number generation; Stochastic process; Randomness; Limit (mathematics); Random variable","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003734706,0.0001583089,0.0001704207,0.00007180616,0.0001354607,0.0001131462,0.0003881842,0.00005667053,0.000104233],"category_scores_gemma":[0.00003200018,0.0001333426,0.0001399549,0.0003250599,0.00003552476,0.0001322659,0.00008137171,0.00007054002,0.0004193493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007290034,"about_ca_system_score_gemma":0.00007047194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001569103,"about_ca_topic_score_gemma":0.00002334646,"domain_scores_codex":[0.9986385,0.00004419001,0.0002798094,0.0004116208,0.0002912509,0.0003346933],"domain_scores_gemma":[0.9991606,0.0001508315,0.00006653448,0.0003963867,0.0001473642,0.00007822482],"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":[0.0003734306,0.001354502,0.001556748,0.0001226733,0.00006825763,0.00004835094,0.0004080072,0.3259602,0.1182306,0.3390925,0.1816626,0.03112216],"study_design_scores_gemma":[0.002713873,0.00004486785,0.0002284198,0.00000757542,0.000008042535,0.0000102722,0.000003958387,0.9247202,0.05999687,0.001742062,0.01028683,0.0002370382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09141404,0.00003359132,0.9033426,0.0005347864,0.0005121507,0.0003518201,0.000004350243,0.0002812711,0.003525411],"genre_scores_gemma":[0.7076,0.000001043109,0.2889348,0.0006881291,0.0005128433,0.00006851913,0.00001438351,0.00002100819,0.002159289],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.616186,"threshold_uncertainty_score":0.5437552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0106935391070136,"score_gpt":0.2493537740336371,"score_spread":0.2386602349266236,"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."}}