{"id":"W2118097554","doi":"10.2307/3315868","title":"Design and analysis of computer experiments when the output is highly correlated over the input space","year":2002,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Realization (probability); Limiting; Gaussian process; Process (computing); Code (set theory); Function (biology); Gaussian; Mathematical optimization; Mathematics; Stochastic process; Applied mathematics; Computer science; Source code; Algorithm; Correlation; Space (punctuation); Statistics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002251083,0.0001160472,0.0002249511,0.0002880983,0.0001806422,0.0001258746,0.0005115454,0.00003844648,0.00008941285],"category_scores_gemma":[0.00007464667,0.00007545517,0.00004646723,0.0005730391,0.0001848284,0.0001967414,0.00003819981,0.0001762324,0.000002873931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009997858,"about_ca_system_score_gemma":0.0001531701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004146729,"about_ca_topic_score_gemma":0.0002232561,"domain_scores_codex":[0.9989586,0.0001374647,0.0003374931,0.0001341192,0.000240184,0.0001921199],"domain_scores_gemma":[0.9983211,0.0003714333,0.0003978632,0.0002723881,0.0004043722,0.0002327992],"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":[0.00001916079,0.00009434682,0.005990012,0.00001260125,0.002942712,0.0004236674,0.07407036,0.6904868,0.00004320704,0.0183078,0.1151537,0.0924556],"study_design_scores_gemma":[0.0003098514,0.00008304098,0.006390146,0.00001152872,0.0001447274,0.00002876901,0.00006899211,0.9907577,0.00005134731,0.000491859,0.001570496,0.0000915425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006167821,0.0004230069,0.9977175,0.000757366,0.000278315,0.0001066822,0.00005612858,0.000003712919,0.00004051115],"genre_scores_gemma":[0.1292259,0.00008054295,0.8693828,0.0009490437,0.00003584002,0.000001290388,0.000001813036,0.00001177187,0.0003110287],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3002709,"threshold_uncertainty_score":0.3076973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02910053586077545,"score_gpt":0.2394130883408413,"score_spread":0.2103125524800658,"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."}}