{"id":"W1578600300","doi":"10.1109/icsmc.1996.561475","title":"Reliability-based optimization on a graph-theoretic modelling foundation","year":2002,"lang":"en","type":"article","venue":"","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Reliability (semiconductor); Mathematical optimization; Graph; Structural reliability; Reliability theory; Graph theory; Reliability engineering; Theoretical computer science; Mathematics; Artificial intelligence; Engineering; Probabilistic logic; Failure rate","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009986279,0.000788639,0.0007597408,0.0007328347,0.0003647375,0.0009002953,0.001114321,0.0007212173,0.00308462],"category_scores_gemma":[0.002426501,0.0006761073,0.0009417039,0.000737073,0.001273002,0.001738802,0.001021643,0.001421866,0.0007005882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00123948,"about_ca_system_score_gemma":0.001347712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001913383,"about_ca_topic_score_gemma":0.002161269,"domain_scores_codex":[0.9993316,0.000243753,0.00002238347,0.00008903058,0.0002679749,0.00004535228],"domain_scores_gemma":[0.9992411,0.000489014,0.00006704045,0.00009902136,0.00008302996,0.00002081309],"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":[0.000007813204,0.000009870328,0.00003703472,0.00003236776,0.000009102586,0.00001452594,0.00001997835,0.709058,0.000842826,0.2811945,0.000554004,0.008219961],"study_design_scores_gemma":[0.000004393863,0.000009461996,0.00002117036,0.000007585083,0.000004209986,0.00000783202,0.000003079149,0.8292227,0.0002697392,0.1685685,0.001876152,0.000005120181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001972679,0.0001020357,0.9939576,0.0001900928,0.00001138055,0.00001304863,0.00003740901,0.000103216,0.003612399],"genre_scores_gemma":[0.4141606,0.001340464,0.5749199,0.0002246497,0.0001118848,0.0004357342,0.0002934762,0.0003877664,0.008125516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00308462,"threshold_uncertainty_score":0.01031911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1029260509629022,"score_gpt":0.2917797444252522,"score_spread":0.18885369346235,"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."}}