{"id":"W4385488238","doi":"10.1109/ecai58194.2023.10194001","title":"Chaotic American zebra search optimization algorithm for benchmark challenges","year":2023,"lang":"en","type":"article","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Chaotic; Benchmark (surveying); Truss; Computer science; Metaheuristic; Swarm intelligence; Algorithm; Swarm behaviour; Bar (unit); Modal; Mathematical optimization; CHAOS (operating system); Artificial intelligence; Mathematics; Engineering; Particle swarm optimization","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":[0.001219415,0.0001793492,0.0002625907,0.0005844149,0.0002258764,0.0002539328,0.001093709,0.00005430321,0.0001555581],"category_scores_gemma":[0.000266675,0.0001663233,0.00008560245,0.002158882,0.0001144833,0.0003941822,0.0004247297,0.0001331722,0.0002641104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005659569,"about_ca_system_score_gemma":0.0001435132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002623878,"about_ca_topic_score_gemma":0.000002659385,"domain_scores_codex":[0.9974164,0.0001663035,0.000305303,0.0006806153,0.0007541281,0.0006771843],"domain_scores_gemma":[0.9979288,0.0005827078,0.00007181037,0.0007185622,0.0004573419,0.0002407529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002634117,0.00005790758,0.000007048667,0.00002939786,0.00003158546,0.000009150539,0.0003743541,0.1170937,0.000007379128,0.01931205,0.003014469,0.8600603],"study_design_scores_gemma":[0.0003403021,0.0001706818,0.0002134432,0.000006404713,0.000003474453,0.000004610888,0.000207437,0.9964839,0.0001276335,0.0005347494,0.001708724,0.0001986273],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00002557792,0.00008407489,0.9894286,0.005939048,0.0002841669,0.0006406476,0.00001040241,0.0006950073,0.002892488],"genre_scores_gemma":[0.001207132,0.001032624,0.99326,0.0001693673,0.0001475025,0.0001779022,0.00005772442,0.00003271,0.003915092],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8793902,"threshold_uncertainty_score":0.6782466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05494683518197453,"score_gpt":0.3236612942362135,"score_spread":0.268714459054239,"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."}}