{"id":"W3162993720","doi":"10.1080/15732479.2020.1832538","title":"Development of a civil infrastructure resilience assessment framework and its application to a nuclear power plant","year":2020,"lang":"en","type":"article","venue":"Structure and Infrastructure Engineering","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fragility; Resilience (materials science); Risk analysis (engineering); Process (computing); Upgrade; Event (particle physics); Computer science; Engineering; Business","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009447594,0.0004987237,0.0005877099,0.0002161256,0.0001514505,0.00007058427,0.0003222109,0.0003220524,0.00016859],"category_scores_gemma":[0.000102351,0.0004571899,0.00006333044,0.0006840368,0.00005567526,0.0002593606,0.0001756838,0.0007199391,0.000001925622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008283615,"about_ca_system_score_gemma":0.0000558953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001459585,"about_ca_topic_score_gemma":0.000006539584,"domain_scores_codex":[0.9979737,0.00001843844,0.000597488,0.0005615429,0.0003905133,0.0004583157],"domain_scores_gemma":[0.9990532,0.00005813567,0.00009229736,0.0002942673,0.00006564028,0.0004364926],"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":[0.00004997828,0.000006000705,0.002097928,0.0009661809,0.0002477829,0.000006465763,0.0114337,0.6135696,0.3390764,0.01750809,0.0003429729,0.01469495],"study_design_scores_gemma":[0.001018844,0.0003403976,0.2376299,0.000449928,0.0002217493,0.0001336945,0.001654934,0.6582313,0.03915628,0.003779799,0.05476927,0.002613863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8577446,0.0003639102,0.1405341,0.0001679722,0.0001815626,0.000442528,0.0001155436,0.0002470628,0.0002027316],"genre_scores_gemma":[0.933616,0.00004040344,0.06588504,0.0002354818,0.0001306865,0.00001312231,0.00002086174,0.00005768673,7.353603e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2999201,"threshold_uncertainty_score":0.999788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003012795481219563,"score_gpt":0.2024631621248439,"score_spread":0.1994503666436243,"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."}}