{"id":"W4281736062","doi":"","title":"Escaping unknown discontinuous regions in blackbox optimization","year":2022,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Classification of discontinuities; Mathematical optimization; Optimization problem; Constraint (computer-aided design); Nonlinear system; Benchmark (surveying); Computer science; Series (stratigraphy); Space (punctuation); Penalty method; Convergence (economics); Feasible region; Key (lock); Mathematics; Algorithm","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":[0.00163227,0.0001672574,0.0002052959,0.0002206967,0.0002900789,0.0000931707,0.0004201783,0.00005405114,0.0001223795],"category_scores_gemma":[0.0003454935,0.0002101791,0.00006573713,0.0007262354,0.00004692248,0.0002662374,0.0001827665,0.0002809883,0.000008376179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002694993,"about_ca_system_score_gemma":0.00003906228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001240221,"about_ca_topic_score_gemma":0.0004776884,"domain_scores_codex":[0.9971488,0.001618804,0.0003984123,0.0003078815,0.0002424347,0.0002836422],"domain_scores_gemma":[0.9984363,0.0003845277,0.0001272521,0.0007077823,0.0002712303,0.00007295008],"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":[0.000003961309,0.00007424145,0.0003272335,0.0000190908,0.00001344205,0.000003354771,0.002765878,0.9648979,0.001013002,0.02538645,0.0001993673,0.005296139],"study_design_scores_gemma":[0.0006557212,2.772967e-7,0.000266393,0.0001505185,0.000008926168,0.00001092346,0.0003159974,0.9897732,0.001118508,0.0004927816,0.006960117,0.0002467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01082323,0.0007141505,0.9565691,0.001413327,0.0001751363,0.0003749931,0.00001378504,0.0004536486,0.02946264],"genre_scores_gemma":[0.9509161,0.0001527807,0.04599208,0.00003365022,0.00001482389,0.0001856711,0.0001816813,0.00006118074,0.002462096],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9400928,"threshold_uncertainty_score":0.8570853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005967160042736057,"score_gpt":0.1854057089834891,"score_spread":0.1794385489407531,"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."}}