{"id":"W2042983033","doi":"10.1115/detc2007-35517","title":"Reliable Space Pursuing for RBDO With Black-Box Performance Functions","year":2007,"lang":"en","type":"article","venue":"","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Black box; Computer science; Computation; Probabilistic logic; Mathematical optimization; Reliability (semiconductor); Point (geometry); Nested loop join; Space (punctuation); Optimization problem; Algorithm; Mathematics; Data mining; Artificial intelligence; Power (physics)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002667739,0.0001224826,0.0001664766,0.0001638617,0.0002096925,0.0001126316,0.0003208402,0.00006172934,0.0002122021],"category_scores_gemma":[0.0007036832,0.0000731011,0.00005151123,0.0006377644,0.00009256618,0.0002653255,0.00003382765,0.00009649756,0.0003024885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004170052,"about_ca_system_score_gemma":0.00006194234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008901793,"about_ca_topic_score_gemma":0.00001773824,"domain_scores_codex":[0.9984132,0.00000762105,0.0003097759,0.0003399801,0.0005577284,0.0003717168],"domain_scores_gemma":[0.9981944,0.0008820799,0.00007133338,0.0004340229,0.0002956883,0.0001225041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007005338,0.0002222528,0.02903088,0.0000831591,0.00008129522,0.00001382263,0.0008337682,0.5994042,0.00169153,0.0830527,0.2513436,0.03354234],"study_design_scores_gemma":[0.002042406,0.001383615,0.02248818,0.0001222413,0.0000785521,0.00006217651,0.003082072,0.3132816,0.007144195,0.007620435,0.6416708,0.001023669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04701838,0.00003048839,0.9176785,0.0003376418,0.0003060687,0.0002442203,0.000002181259,0.0001230267,0.03425952],"genre_scores_gemma":[0.8209944,0.00000380247,0.1015817,0.00008961518,0.0001313913,0.00001383038,0.000001629075,0.00001632835,0.07716726],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8160967,"threshold_uncertainty_score":0.3887979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05874408360609289,"score_gpt":0.3026771026564616,"score_spread":0.2439330190503687,"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."}}