{"id":"W4417382663","doi":"10.1145/3785134","title":"Algorithm 1060: EDOLAB, a Platform for Research and Education in Evolutionary Dynamic Optimization","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Mathematical Software","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Natural Science Foundation of China","keywords":"Benchmark (surveying); Suite; Consistency (knowledge bases); MATLAB; Evolutionary algorithm; Optimization problem; Genetic algorithm","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":[0.0003763629,0.0001689572,0.0002043983,0.0006614736,0.0003849524,0.0001039477,0.0004974168,0.0001426173,0.00002760425],"category_scores_gemma":[0.0006183657,0.0001714286,0.00005088605,0.001193387,0.0001222218,0.0006708481,0.00004251557,0.00031322,0.00001369355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004047281,"about_ca_system_score_gemma":0.0003752039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005632461,"about_ca_topic_score_gemma":0.0000067084,"domain_scores_codex":[0.9984527,0.00005781496,0.0003447133,0.0005215249,0.0002891292,0.0003341059],"domain_scores_gemma":[0.99754,0.001301931,0.00005001109,0.0005926279,0.0004242662,0.0000911813],"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":[0.00002101853,0.0007647101,0.000008895286,0.0001045882,0.00001683316,8.508791e-7,0.0002229494,0.0705459,0.00000589872,0.00523277,0.00002209259,0.9230535],"study_design_scores_gemma":[0.0004665351,0.00007900271,0.0001047628,0.0001315849,0.00000534931,0.000006232621,0.0001278263,0.5486184,0.00004931325,0.4502072,0.00009077297,0.0001130111],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00009419607,0.0001137915,0.9973306,0.0009449519,0.0001820452,0.00104764,0.0000204212,0.0001859563,0.00008036982],"genre_scores_gemma":[0.0008403427,0.00006451058,0.9964931,0.000117467,0.00001057323,0.0005928086,0.00001836813,0.00001806377,0.001844783],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9229405,"threshold_uncertainty_score":0.6990655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03034314955807717,"score_gpt":0.3628512883966522,"score_spread":0.3325081388385751,"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."}}