{"id":"W4402147782","doi":"","title":"A study of quadratic search step formulations for multiobjective derivative free optimization","year":2022,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Derivative (finance); Mathematical optimization; Quadratic equation; Mathematics; Quadratic model; Computer science; Multi-objective optimization; Statistics; Response surface methodology","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":[0.003325308,0.001154493,0.0007439932,0.0005407138,0.0003948766,0.001237797,0.001198149,0.001335823,0.006645944],"category_scores_gemma":[0.01012114,0.0005099752,0.0009139974,0.0008489386,0.0009146024,0.00149362,0.001129503,0.002258813,0.0003876636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006704457,"about_ca_system_score_gemma":0.0008789197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278729,"about_ca_topic_score_gemma":0.001221227,"domain_scores_codex":[0.9992294,0.0004622311,0.00002470767,0.00005544961,0.0001926371,0.00003566968],"domain_scores_gemma":[0.9947514,0.004451184,0.0001736294,0.0001451994,0.0003834616,0.00009515402],"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":[0.0001177279,0.0001688017,0.0002749164,0.0005394516,0.0000617596,0.0001428681,0.0001758628,0.7301224,0.002092188,0.2237549,0.00314748,0.03940167],"study_design_scores_gemma":[0.0000104771,0.00007741382,0.00006965399,0.0000228937,0.000008528959,0.00001974183,0.00001158146,0.9812042,0.0002569388,0.01721874,0.001094716,0.000005023316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01284919,0.0008723818,0.9680966,0.0004640357,0.0001234349,0.0000988877,0.00003952523,0.00005027248,0.01740574],"genre_scores_gemma":[0.5384207,0.001695878,0.4274326,0.0005041605,0.0002172376,0.0004887716,0.0001716049,0.0003800263,0.03068901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006645944,"threshold_uncertainty_score":0.02223289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02054731754040324,"score_gpt":0.265510700406384,"score_spread":0.2449633828659807,"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."}}