{"id":"W4396494576","doi":"10.18280/ts.410220","title":"Optimization of Acoustic Entropy Source for Random Sequence Generation Using an Improved Grey Wolf Algorithm","year":2024,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Speech and Audio Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Algorithm; Sequence (biology); Entropy (arrow of time); Computer science; Random sequence; Mathematics; Physics; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008307829,0.000671146,0.0008376138,0.0007564033,0.0002509364,0.0006266951,0.0008085215,0.0008384302,0.00177058],"category_scores_gemma":[0.002153786,0.0002972772,0.0005756269,0.0004510711,0.0004968328,0.0005623499,0.0006086616,0.0005835582,0.0003431955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005428202,"about_ca_system_score_gemma":0.001019592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002769907,"about_ca_topic_score_gemma":0.002312083,"domain_scores_codex":[0.9996229,0.00007693153,0.0000243873,0.00007636561,0.0001510981,0.00004822293],"domain_scores_gemma":[0.9995022,0.0002637967,0.00006061812,0.00002707566,0.000125707,0.0000206168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001067968,0.00005881463,0.0009541565,0.00009403392,0.00003777456,0.0001064063,0.0000831775,0.8929757,0.01212647,0.005509572,0.0008554027,0.08709165],"study_design_scores_gemma":[0.0000115073,0.00002406047,0.0001062974,0.000004012022,0.000004448355,0.00001124222,0.000004199065,0.9977111,0.001263337,0.000600946,0.0002552272,0.000003677982],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04177305,0.0003482616,0.9537485,0.0001804784,0.00004568416,0.0001021913,0.00004240094,0.0005973174,0.00316214],"genre_scores_gemma":[0.5861567,0.0002470353,0.4091811,0.0001581582,0.00003114768,0.0003768691,0.000207223,0.0001286987,0.003512992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002769907,"threshold_uncertainty_score":0.005923212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03744770999204726,"score_gpt":0.2766180691435586,"score_spread":0.2391703591515114,"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."}}