{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004760855,0.0005155769,0.0005133132,0.000587539,0.0003218978,0.000418735,0.000668624,0.0005641559,0.001260401],"category_scores_gemma":[0.001154925,0.0001907497,0.0004416009,0.0005040886,0.0003619972,0.0004924597,0.0006330687,0.0004919708,0.0002239869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003537944,"about_ca_system_score_gemma":0.000699073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002461093,"about_ca_topic_score_gemma":0.002094005,"domain_scores_codex":[0.9997818,0.0000785168,0.00001318066,0.00003017768,0.00007293856,0.00002338462],"domain_scores_gemma":[0.9997991,0.00008769205,0.00002169769,0.00002069608,0.00005920884,0.00001159583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001020019,0.00003234936,0.001071786,0.00008330474,0.00006580741,0.00005202141,0.00007036711,0.8844199,0.00476088,0.0210612,0.001307586,0.08697297],"study_design_scores_gemma":[0.00001157684,0.00003181443,0.0000901901,0.000003431583,0.000005899451,0.00001259627,0.000007462187,0.9965273,0.0005365962,0.001561591,0.001208206,0.000003371629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04889813,0.0004281918,0.9432952,0.0001743333,0.0000666703,0.0000630237,0.00003202459,0.0003345085,0.006707997],"genre_scores_gemma":[0.6256576,0.0003400459,0.3679289,0.000122346,0.0000439801,0.000290825,0.0001489629,0.00009509979,0.005372227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002461093,"threshold_uncertainty_score":0.004893482,"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."}}