{"id":"W3007184626","doi":"10.1016/j.rtbm.2020.100452","title":"Resilience of cities towards airport disruptions at global scale","year":2020,"lang":"en","type":"article","venue":"Research in Transportation Business & Management","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Resilience (materials science); Port (circuit theory); Transport engineering; Business; Catchment area; Urban resilience; Scale (ratio); Environmental planning; Regional science; Geography; Civil engineering; Urban planning; Engineering; Drainage basin","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":[0.001556667,0.0001104719,0.0002031093,0.0001361192,0.0003331383,0.00004339786,0.0004604036,0.00006689864,0.0003060795],"category_scores_gemma":[0.00003284746,0.0001145056,0.00006548437,0.002936965,0.000722577,0.000534548,0.00002331822,0.000129076,0.00001560188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002556479,"about_ca_system_score_gemma":0.0001950193,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.006676676,"about_ca_topic_score_gemma":0.04616556,"domain_scores_codex":[0.9970871,0.0001164735,0.0005046691,0.0004094176,0.001383817,0.0004985827],"domain_scores_gemma":[0.9991037,0.00004332545,0.00008578977,0.0002020053,0.0003812399,0.0001838997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002049093,0.0001875815,0.9624807,0.0006019019,0.00001651974,0.00008685007,0.006884552,0.0004543567,0.00005348072,0.01320005,0.0002541548,0.01557499],"study_design_scores_gemma":[0.0003224676,0.00001202863,0.9878976,0.00008796841,0.00001377916,2.683703e-8,0.005523258,0.00001437786,0.00007207468,0.001809479,0.004138667,0.0001082827],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686155,0.0001615074,0.001591892,0.006246109,0.00009346114,0.0006985983,0.00007836403,0.00005975293,0.0224548],"genre_scores_gemma":[0.9984151,0.0005099067,0.0004478398,0.000042683,0.00006205987,0.00005048139,0.00008216903,0.000007686924,0.0003820352],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03948888,"threshold_uncertainty_score":0.999938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09036401741352708,"score_gpt":0.4010806801542568,"score_spread":0.3107166627407297,"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."}}