{"id":"W2761792028","doi":"10.3390/e19100533","title":"Cross Entropy Method Based Hybridization of Dynamic Group Optimization Algorithm","year":2017,"lang":"en","type":"article","venue":"Entropy","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Universidade de Macau","keywords":"Algorithm; Group (periodic table); Mathematics; Optimization algorithm; Entropy (arrow of time); Computer science; Mathematical optimization; Physics; Thermodynamics","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":[0.001015146,0.0002097219,0.0003166879,0.0002539438,0.0005137105,0.0007796119,0.001900451,0.0000934281,0.0003787094],"category_scores_gemma":[0.0009038157,0.0002071239,0.0001174571,0.0003149958,0.0001993962,0.0009588848,0.0003951439,0.000169186,0.00004027173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001116203,"about_ca_system_score_gemma":0.0001515348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005122703,"about_ca_topic_score_gemma":0.000001227404,"domain_scores_codex":[0.9972975,0.000331234,0.0005097609,0.0005993237,0.0008535873,0.0004085733],"domain_scores_gemma":[0.9968202,0.0001748405,0.0005915556,0.001693776,0.0005489258,0.0001707375],"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":[0.00004292294,0.0004149914,0.0009367306,0.00007662416,0.00008308488,0.00004463886,0.00013869,0.7148475,0.001664278,0.04497599,0.0002706272,0.2365039],"study_design_scores_gemma":[0.001225607,0.00008404043,0.00205747,0.00001916102,0.00001117355,0.000005555657,0.000002925314,0.9909214,0.004423982,0.0007163934,0.0003401755,0.0001921237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001176772,0.00004602175,0.9977093,0.0006142002,0.0006243761,0.0003732422,0.00002733337,0.0001241457,0.0003636653],"genre_scores_gemma":[0.02691383,0.00004769113,0.972231,0.00006610552,0.0000697227,0.00002815345,0.00006281059,0.00002711767,0.0005535762],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2760739,"threshold_uncertainty_score":0.8446269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686837621253734,"score_gpt":0.3407139876585352,"score_spread":0.3238456114459978,"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."}}