{"id":"W3195734723","doi":"10.22266/ijies2021.1031.12","title":"TIMBO: Three Influential Members Based Optimizer","year":2021,"lang":"en","type":"article","venue":"International journal of intelligent engineering and systems","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Particle swarm optimization; Mathematical optimization; Computer science; Population; Optimization problem; Genetic algorithm; Meta-optimization; Derivative-free optimization; Algorithm; Mathematics","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":[0.001304456,0.001405895,0.001438032,0.001004343,0.001160279,0.001328586,0.00218115,0.001649244,0.004138952],"category_scores_gemma":[0.001846895,0.0005182308,0.001165426,0.0008895445,0.0007682003,0.001026787,0.001510866,0.001553807,0.00129939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008579874,"about_ca_system_score_gemma":0.001414444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004636823,"about_ca_topic_score_gemma":0.003659356,"domain_scores_codex":[0.9991395,0.0002244274,0.00003337289,0.0001079442,0.0004188584,0.00007580998],"domain_scores_gemma":[0.9995344,0.0001408909,0.00007165366,0.00004332226,0.0001588548,0.00005096579],"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":[0.0002182033,0.0001322067,0.001099521,0.0001846892,0.0001563721,0.0001231064,0.0001545388,0.8030255,0.005740699,0.01451478,0.006606854,0.1680434],"study_design_scores_gemma":[0.00002636378,0.0000520112,0.000154106,0.00001228817,0.00001860366,0.00003273746,0.00001354402,0.9924834,0.001253397,0.002026191,0.003912494,0.00001475107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006608606,0.0003016668,0.9857276,0.0001166666,0.00006127821,0.00009420922,0.00003800923,0.0008007559,0.006251257],"genre_scores_gemma":[0.3715768,0.0007913467,0.6091763,0.0004859236,0.0001369639,0.001113706,0.0004772015,0.0006313313,0.0156106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004636823,"threshold_uncertainty_score":0.01384616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02104300154923021,"score_gpt":0.2707755087993766,"score_spread":0.2497325072501463,"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."}}