{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01828178,0.00086478,0.001449969,0.0006365567,0.0004041423,0.001190178,0.001062593,0.001280672,0.0009922514],"category_scores_gemma":[0.06868476,0.0009583795,0.0004705408,0.0004540687,0.001892668,0.001007549,0.0009293309,0.001054092,0.0001184593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00142938,"about_ca_system_score_gemma":0.001758954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008215569,"about_ca_topic_score_gemma":0.0006834551,"domain_scores_codex":[0.986252,0.01084965,0.0003424714,0.00101138,0.001041404,0.0005029935],"domain_scores_gemma":[0.8878528,0.1012214,0.004835045,0.002557552,0.002955891,0.000577295],"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":[0.004370244,0.0005138603,0.003787245,0.0003859127,0.000287944,0.0001073757,0.0000814706,0.918646,0.008537513,0.0198101,0.0003792757,0.04309301],"study_design_scores_gemma":[0.0002037697,0.0006996496,0.0007660321,0.00001866065,0.0000468876,0.00001424796,0.0000133292,0.9838901,0.005921984,0.008118141,0.0002931191,0.00001407326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1573671,0.0003943577,0.839283,0.0002921204,0.00005116747,0.0007269788,0.00006685465,0.0005037763,0.001314537],"genre_scores_gemma":[0.7600467,0.000165012,0.2372633,0.0001098277,0.00003596635,0.0017742,0.0001015886,0.00004636714,0.0004570472],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01828178,"threshold_uncertainty_score":0.09668452,"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."}}