{"id":"W3134041587","doi":"10.1007/s10589-020-00249-0","title":"Stochastic mesh adaptive direct search for blackbox optimization using probabilistic estimates","year":2021,"lang":"en","type":"article","venue":"Computational Optimization and Applications","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Polytechnique Montréal; Group for Research in Decision Analysis","funders":"","keywords":"Mathematics; Mathematical optimization; Probabilistic logic; Martingale (probability theory); Convergence (economics); Extension (predicate logic); Stochastic optimization; Convergence of random variables; Algorithm; Random variable; Computer science; Applied 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":[0.002749641,0.0009735674,0.002150409,0.001200226,0.0006363367,0.001422385,0.001717443,0.002302674,0.003990265],"category_scores_gemma":[0.01076826,0.001232644,0.0009720594,0.0009938926,0.001443508,0.00157016,0.002168152,0.001731016,0.0005215115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001230769,"about_ca_system_score_gemma":0.001601816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004248273,"about_ca_topic_score_gemma":0.004015544,"domain_scores_codex":[0.9992663,0.0003946965,0.00002584562,0.00007966555,0.0001826358,0.00005079623],"domain_scores_gemma":[0.9945628,0.004446123,0.0002991701,0.0001908554,0.0003744164,0.0001266719],"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":[0.00004149922,0.00002135681,0.0001161734,0.00004029767,0.00002917026,0.00001627073,0.00001251649,0.9796723,0.0002472893,0.01380696,0.000333293,0.005662845],"study_design_scores_gemma":[0.000003857946,0.00000309203,0.000008462597,0.000002578627,0.000001347934,0.000001088192,8.071144e-7,0.9979366,0.00003199656,0.001951741,0.00005753211,0.000001024539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006847608,0.0002149267,0.9898731,0.0001651565,0.00005655708,0.0000401083,0.00003229367,0.0001320787,0.00263818],"genre_scores_gemma":[0.5487754,0.0004489881,0.4412422,0.0002434418,0.000141997,0.0006178655,0.0002113413,0.0003394756,0.007979165],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004248273,"threshold_uncertainty_score":0.01454163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04944740018437694,"score_gpt":0.3263624437658484,"score_spread":0.2769150435814715,"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."}}