{"id":"W1925813256","doi":"10.1007/s11081-015-9283-0","title":"Dynamic scaling in the mesh adaptive direct search algorithm for blackbox optimization","year":2015,"lang":"en","type":"article","venue":"Optimization and Engineering","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis","funders":"Air Force Office of Scientific Research; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Convergence (economics); Algorithm; Benchmark (surveying); Mathematical optimization; Adaptive mesh refinement; Scale (ratio); Computational science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000928715,0.0001836932,0.0002156429,0.0002596577,0.0001005176,0.0001061685,0.0001672454,0.00009866381,0.00001602727],"category_scores_gemma":[0.0005538526,0.0001592763,0.00003799728,0.0006071398,0.00003667448,0.0003138495,0.00005212882,0.0001836435,0.000001307114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001388827,"about_ca_system_score_gemma":0.00005174293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000507013,"about_ca_topic_score_gemma":0.00000204856,"domain_scores_codex":[0.998666,0.00007636919,0.0002979995,0.0002784559,0.0003465722,0.000334529],"domain_scores_gemma":[0.9989243,0.0004391402,0.00005348928,0.000199041,0.0002683579,0.0001156343],"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":[0.00001164964,0.00003428194,0.000004887153,0.00002608931,0.00001265943,0.000002119409,0.001028015,0.9948745,0.000002492186,0.0007491619,0.00005464783,0.003199434],"study_design_scores_gemma":[0.0009207067,0.00005089762,0.000005861005,0.00004024334,0.0000123223,0.000008499769,0.001001073,0.9974958,0.00002332057,0.0001696365,0.00008813206,0.0001835385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001530337,0.0001045933,0.9981444,0.0001804336,0.00008565674,0.0007439996,0.00001518968,0.0001156547,0.0004569883],"genre_scores_gemma":[0.006845132,0.0001645315,0.9924545,0.0000341944,0.00004513442,0.0001382227,0.00006200292,0.00006061607,0.0001956121],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006692098,"threshold_uncertainty_score":0.64951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0474526428482866,"score_gpt":0.323116341158649,"score_spread":0.2756636983103624,"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."}}