{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001203018,0.001138805,0.0009651507,0.001077254,0.0006549744,0.0008133577,0.001871031,0.0007124348,0.06319012],"category_scores_gemma":[0.002525268,0.000637442,0.0009692222,0.000981994,0.0003345445,0.0009315135,0.0009855636,0.00215826,0.01663103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000539418,"about_ca_system_score_gemma":0.001491724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002400363,"about_ca_topic_score_gemma":0.002205066,"domain_scores_codex":[0.9994449,0.0001251821,0.00003955971,0.00009815355,0.0002259366,0.00006628632],"domain_scores_gemma":[0.9987279,0.0005769038,0.00005822599,0.0001917883,0.0003976036,0.00004751733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003779,0.0004351386,0.002337832,0.0008057408,0.0002907638,0.0003696272,0.0002880505,0.2712273,0.01838256,0.09229127,0.2013633,0.4118304],"study_design_scores_gemma":[0.0002205766,0.00006916521,0.0008701176,0.0000593086,0.0000443758,0.0001912096,0.00002449555,0.8559145,0.009216213,0.02900774,0.1043363,0.00004594299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00216167,0.00005919842,0.9589356,0.00007623762,0.00004607143,0.0002196089,0.002194412,0.02706615,0.009241127],"genre_scores_gemma":[0.04200984,0.0001531006,0.9309787,0.0001318913,0.00004781716,0.002416047,0.005253694,0.006156386,0.0128525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06319012,"threshold_uncertainty_score":0.211392,"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."}}