{"id":"W3182786887","doi":"10.1145/3449726.3463186","title":"Population-based coordinate descent algorithm with majority voting","year":2021,"lang":"en","type":"article","venue":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Population; Coordinate descent; Voting; Mathematical optimization; Algorithm; Scale (ratio); 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":[0.002191014,0.001373452,0.002754998,0.0008333065,0.0008877005,0.001311379,0.003258251,0.001718747,0.002167206],"category_scores_gemma":[0.003937976,0.0005358986,0.0009714234,0.001341704,0.0009281677,0.001039889,0.001359166,0.001404636,0.0009750053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008174092,"about_ca_system_score_gemma":0.001901097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006934421,"about_ca_topic_score_gemma":0.005339149,"domain_scores_codex":[0.9983106,0.000607927,0.00008023975,0.0003109433,0.000527121,0.000163209],"domain_scores_gemma":[0.9986099,0.0004301404,0.0001218162,0.0001458679,0.0006261222,0.00006612718],"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":[0.0001522369,0.00008953481,0.001525537,0.0001219443,0.0001470465,0.00012753,0.0001386976,0.7648678,0.003171286,0.01810895,0.006427372,0.2051221],"study_design_scores_gemma":[0.00004098938,0.00005167351,0.0001165592,0.000005976699,0.00001454199,0.00002749819,0.000009827849,0.9955669,0.0006167617,0.00210542,0.001435653,0.000008238968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008643768,0.0003325959,0.9868878,0.0001746873,0.00009726924,0.0001076133,0.00003007501,0.0004132758,0.003312856],"genre_scores_gemma":[0.4190025,0.0004446482,0.5690428,0.0003870465,0.0001474874,0.0007648749,0.0003529378,0.0001711194,0.009686511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006934421,"threshold_uncertainty_score":0.01378816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01890787756790012,"score_gpt":0.2438035057147521,"score_spread":0.224895628146852,"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."}}