{"id":"W3033575772","doi":"10.1155/2020/1369591","title":"A Comparative Study on Flight Delay Networks of the USA and China","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Betweenness centrality; Centrality; Complex network; Computer science; Benchmark (surveying); Air traffic control; Aviation; Construct (python library); Engineering; Computer network; Geography; Mathematics; Aerospace engineering; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001214447,0.00007240911,0.0003859693,0.00005077259,0.00004855186,0.00001044106,0.00008822282,0.00001870803,0.00004514966],"category_scores_gemma":[0.000008400651,0.00005477783,0.0001163692,0.0002307379,0.00002005715,0.0001405407,0.000002388168,0.0001119745,0.000001582281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001133979,"about_ca_system_score_gemma":0.000005766109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003708238,"about_ca_topic_score_gemma":0.0001738071,"domain_scores_codex":[0.9991366,0.00001388082,0.0006384227,0.0001010587,0.00004888018,0.00006120528],"domain_scores_gemma":[0.9989941,0.00002143926,0.0008217597,0.0000747221,0.0000460479,0.00004198546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0005411819,0.0003288663,0.4652558,0.00004251263,0.0005671576,0.0000132988,0.03158652,0.4825134,0.0002409229,0.01795989,0.00006902087,0.0008814779],"study_design_scores_gemma":[0.0007043798,0.0005258099,0.9945967,0.00001908307,0.00003329215,0.000001171036,0.001147508,0.001474143,0.00003680287,0.0004307932,0.0009688154,0.0000614752],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947939,0.0004774361,0.003954904,0.0002921939,0.0001136017,0.0001308238,0.00001675131,0.0000015666,0.0002188414],"genre_scores_gemma":[0.9996282,0.00004530829,0.0002064193,0.00003922406,0.00005355154,0.000001326165,0.000001316762,0.00000480509,0.00001978982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.529341,"threshold_uncertainty_score":0.2233775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02872631856999529,"score_gpt":0.2397330389197606,"score_spread":0.2110067203497654,"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."}}