{"id":"W4313299845","doi":"10.1287/moor.2022.1344","title":"Error Analysis of Surrogate Models Constructed Through Operations on Submodels","year":2022,"lang":"en","type":"article","venue":"Mathematics of Operations Research","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Black box; Chen; Mathematics; Function (biology); Mathematical optimization; Surrogate model; Computer science; Algorithm; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001195224,0.0001436808,0.0004345602,0.00113002,0.0007878434,0.0001037838,0.001090681,0.00004572105,0.000299126],"category_scores_gemma":[0.000352392,0.0001421633,0.0001232785,0.004956095,0.0002483535,0.0007661316,0.0006289752,0.0003798164,0.000007476451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001580212,"about_ca_system_score_gemma":0.0003432021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001484828,"about_ca_topic_score_gemma":0.00007403705,"domain_scores_codex":[0.9968437,0.0004425371,0.0006761607,0.0004090511,0.001330602,0.000297972],"domain_scores_gemma":[0.9967446,0.0004649364,0.00007844862,0.001087738,0.00155614,0.00006816487],"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":[0.000003851861,0.0003497831,0.000002691917,0.000009652283,0.0001369001,0.000001256002,0.003564543,0.653452,0.0009323559,0.3414443,0.00001818001,0.00008451486],"study_design_scores_gemma":[0.0003246442,0.0001605721,0.00001106249,0.000009321041,0.00003959747,0.000003651738,0.001543282,0.9868362,0.003530399,0.007406977,0.00001291501,0.0001213622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03714532,0.00003138962,0.9591992,0.0003210975,0.00005107023,0.0006405224,0.0002232061,0.00004872974,0.002339436],"genre_scores_gemma":[0.5128616,0.00001463473,0.4864533,0.00002052867,0.000004275812,0.0001716829,0.00005312824,0.00001261979,0.0004082073],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4757163,"threshold_uncertainty_score":0.6059534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1705759330340063,"score_gpt":0.416556545346156,"score_spread":0.2459806123121497,"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."}}