{"id":"W2584716897","doi":"10.1680/jinam.16.00013","title":"Building resilience in virtual and physical networked operations","year":2017,"lang":"en","type":"article","venue":"Infrastructure Asset Management","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Resilience (materials science); Computer science; Context (archaeology); Intersection (aeronautics); Situated; Cascading failure; Risk analysis (engineering); Socio-ecological system; Computer security; Engineering; Business; Geography; Software engineering; Artificial intelligence; Transport engineering; Electric power system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001603747,0.0002125431,0.0002461464,0.0001517241,0.0003563641,0.0003234031,0.0004494168,0.00007218996,0.00003266719],"category_scores_gemma":[0.00003426877,0.0001964849,0.00005012918,0.0001557641,0.0001533994,0.0004791663,0.000197949,0.0002766604,0.000005688904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007936604,"about_ca_system_score_gemma":0.000007674647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003291164,"about_ca_topic_score_gemma":0.0001538518,"domain_scores_codex":[0.9988723,0.00002821354,0.0002227788,0.0003262353,0.0002123805,0.0003380327],"domain_scores_gemma":[0.9992084,0.00002704814,0.00003344399,0.0006336856,0.00001999323,0.0000774553],"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":[0.000004886163,0.000007779319,0.005574044,0.00003257591,0.00004677515,0.00002002671,0.0001644769,0.9235091,0.0007057728,0.009745393,0.0003988088,0.05979037],"study_design_scores_gemma":[0.000393639,0.00002701086,0.3305492,0.00004893481,0.00004831047,0.000006035505,0.0002536793,0.6591272,0.0004132109,0.007157066,0.001654504,0.0003212731],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9545219,0.00003700789,0.0403946,0.0001254178,0.0002343562,0.000216741,0.000005913206,0.00008410321,0.004379964],"genre_scores_gemma":[0.9950929,0.0000654291,0.00454666,0.00004564259,0.0001513357,0.00002584998,0.00000460923,0.00001652937,0.00005106739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3249751,"threshold_uncertainty_score":0.801242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004462761475171022,"score_gpt":0.250812749479024,"score_spread":0.246349988003853,"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."}}