{"id":"W2039638270","doi":"10.1061/(asce)cp.1943-5487.0000204","title":"Computer Program for Multimodel Reliability and Optimization Analysis","year":2012,"lang":"en","type":"article","venue":"Journal of Computing in Civil Engineering","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":159,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Killam Trusts","keywords":"Computer science; Reliability (semiconductor); Scripting language; Computer program; Computation; Program analysis; Probabilistic logic; Software; Reliability engineering; Distributed computing; Artificial intelligence; Engineering; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005036513,0.0001244609,0.0004269199,0.0006145056,0.00003843283,0.0000909146,0.0002341956,0.00006955797,0.000005187002],"category_scores_gemma":[0.001865715,0.00009630657,0.0001597047,0.0008779067,0.00001987741,0.0002909038,0.0000594306,0.0001789027,3.546744e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006363655,"about_ca_system_score_gemma":0.00002232907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001756671,"about_ca_topic_score_gemma":0.000001038075,"domain_scores_codex":[0.9982722,0.00004781794,0.0008575158,0.0001570545,0.000392567,0.0002728029],"domain_scores_gemma":[0.9974493,0.001667181,0.0002729064,0.0001727242,0.0003052572,0.0001325751],"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":[0.000008004011,0.00006844023,0.01009354,0.00002013434,0.0000456906,7.51856e-7,0.0003028935,0.9825178,0.000009084357,0.0001301549,0.00004726098,0.006756238],"study_design_scores_gemma":[0.0003206178,0.00007900494,0.02818518,0.00003918088,0.00006138839,0.00001320379,0.0000177182,0.9709117,0.000006064867,0.00007539128,0.000186947,0.0001035725],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1108682,0.0001554869,0.888366,0.00003634315,0.0003803248,0.0001491239,8.893537e-7,0.00002834713,0.00001532463],"genre_scores_gemma":[0.5649539,0.000002837053,0.4348864,0.000005212954,0.000141071,0.000001369918,3.795583e-7,0.000006309592,0.000002460039],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4540858,"threshold_uncertainty_score":0.3927268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04211673820685264,"score_gpt":0.3237734632776799,"score_spread":0.2816567250708272,"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."}}