{"id":"W4413217170","doi":"10.1145/3712255.3734303","title":"BEACON: Continuous Bi-objective Benchmark problems with Explicit Adjustable COrrelatioN control","year":2025,"lang":"en","type":"article","venue":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Foreign, Commonwealth and Development Office; International Development Research Centre","keywords":"Benchmark (surveying); Computer science; Correlation; Control (management); Mathematics; Artificial intelligence; Geometry; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002307005,0.0009831645,0.0007940438,0.0007680894,0.0002856418,0.0009677163,0.001379404,0.001021259,0.001933611],"category_scores_gemma":[0.007667942,0.0003547244,0.0005595253,0.0006539655,0.0009273783,0.0007972586,0.001375363,0.001571512,0.0003205601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005675943,"about_ca_system_score_gemma":0.001016229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00164015,"about_ca_topic_score_gemma":0.001488234,"domain_scores_codex":[0.9990227,0.000399265,0.00004650647,0.0001155355,0.0003239016,0.00009197144],"domain_scores_gemma":[0.9968691,0.002096631,0.0002896218,0.0002360513,0.0003653747,0.0001431458],"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":[0.0001008053,0.00007105184,0.0004722103,0.00009112784,0.00002465211,0.00003882744,0.00002159667,0.9710692,0.001754146,0.007693195,0.0008400392,0.01782329],"study_design_scores_gemma":[0.00002461836,0.00006622729,0.0001024468,0.000008013484,0.000003528579,0.000008160516,0.000006343536,0.9957411,0.0007835235,0.002844503,0.0004065221,0.000004994221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06495704,0.0004156671,0.9269068,0.0002836954,0.00009993369,0.0001719699,0.0001943159,0.0008843399,0.006086195],"genre_scores_gemma":[0.6879744,0.0001789676,0.3077587,0.0001731204,0.00003243515,0.0005496264,0.0004482875,0.0002546306,0.002629837],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002307005,"threshold_uncertainty_score":0.01220077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007286590246987096,"score_gpt":0.212496243642684,"score_spread":0.2052096533956969,"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."}}