{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001825819,0.001402303,0.0008129408,0.001116311,0.0004199244,0.001451671,0.002810471,0.001291079,0.04009878],"category_scores_gemma":[0.007450499,0.0005497265,0.0007593185,0.0009430058,0.0005667563,0.001617298,0.00235398,0.002257585,0.01546331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006183591,"about_ca_system_score_gemma":0.00186095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002142975,"about_ca_topic_score_gemma":0.003575135,"domain_scores_codex":[0.9992545,0.0001827035,0.000060916,0.0001412948,0.0002943056,0.00006627748],"domain_scores_gemma":[0.9984344,0.0008517217,0.0001168159,0.0002280225,0.0002654836,0.0001035963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009315563,0.0005323649,0.002674928,0.001841481,0.0002550109,0.0003764151,0.0002681079,0.1858237,0.01297338,0.06647216,0.3480193,0.3798317],"study_design_scores_gemma":[0.0007152655,0.0001940379,0.0007914373,0.000189394,0.00004272846,0.0002463167,0.00003576118,0.7109838,0.01040576,0.03478653,0.2415165,0.00009237976],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.005770462,0.001168042,0.8149617,0.000934509,0.0004105138,0.0003188314,0.006254787,0.1434012,0.02678007],"genre_scores_gemma":[0.05685782,0.001145037,0.8846599,0.0008589185,0.0000920478,0.001562532,0.01569837,0.02365495,0.01547034],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04009878,"threshold_uncertainty_score":0.1341438,"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."}}