{"id":"W2599510761","doi":"10.1061/9780784480458.022","title":"Resilience of a Transportation Network from a Geotechnical Perspective","year":2017,"lang":"en","type":"article","venue":"Geotechnical Frontiers 2017","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Resilience (materials science); Sustainability; Natural disaster; Work (physics); Civil engineering; Perspective (graphical); Transportation infrastructure; Environmental planning; Climate change; Psychological resilience; Engineering; Environmental resource management; Construction engineering; Computer science; Transport engineering; Risk analysis (engineering); Business; Environmental science; Geography; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007568225,0.000437539,0.000198815,0.002357531,0.001293272,0.001950344,0.0006994458,0.0007652766,0.002399018],"category_scores_gemma":[0.003013006,0.0001551549,0.0003360749,0.001650755,0.003720894,0.002065245,0.001773349,0.0003645475,0.00008931169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008150534,"about_ca_system_score_gemma":0.003382251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1315205,"about_ca_topic_score_gemma":0.1395962,"domain_scores_codex":[0.9995023,0.0001471366,0.000019729,0.00005893009,0.0001190704,0.0001528029],"domain_scores_gemma":[0.9990281,0.0003143001,0.0002411507,0.00008713236,0.0001919099,0.000137486],"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":[0.00004954873,0.00004047035,0.04839187,0.0001256877,0.00009563893,0.001464311,0.002728869,0.5290688,0.003353342,0.3957966,0.001596217,0.0172887],"study_design_scores_gemma":[0.00001549608,0.0001964281,0.124213,0.0003576414,0.0001636019,0.001344013,0.03066215,0.5698172,0.001848591,0.2451344,0.02614007,0.0001072249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8115531,0.0006223125,0.1045771,0.002754645,0.00002706422,0.0001667671,0.0008777193,0.0001261086,0.07929525],"genre_scores_gemma":[0.9978198,0.0001026049,0.0013841,0.00001001681,0.000002294404,0.00001897253,0.00002997695,0.00000276375,0.0006294493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1315205,"threshold_uncertainty_score":0.26151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007719876513529805,"score_gpt":0.2418386195417315,"score_spread":0.2341187430282017,"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."}}