{"id":"W4382193042","doi":"10.1155/2023/5676795","title":"Synergetic Development Measure of Airport Groups Composite System and Its Influencing Factors Analysis: Some Evidence from China","year":2023,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities; Civil Aviation Administration of China; National College Students Innovation and Entrepreneurship Training Program; Natural Science Foundation of Hubei Province; National Science Foundation","keywords":"Spillover effect; Degree (music); Econometric model; Construct (python library); China; Aviation; Econometrics; Operations research; Computer science; Transport engineering; Mathematics; Geography; Economics; Engineering; Microeconomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001541046,0.0004502671,0.0003183247,0.003668205,0.0006395775,0.001007646,0.0003840901,0.0002120389,0.002911146],"category_scores_gemma":[0.002881566,0.0001838628,0.001089865,0.003580008,0.0007534017,0.001228248,0.001154064,0.0003153825,0.0001370748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002128624,"about_ca_system_score_gemma":0.002057225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02526521,"about_ca_topic_score_gemma":0.02968382,"domain_scores_codex":[0.9990293,0.0002174701,0.00008592054,0.000191435,0.0003349143,0.0001410181],"domain_scores_gemma":[0.9978831,0.0006196135,0.0004197631,0.0001732012,0.000589819,0.0003144286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001024363,0.0001270138,0.931886,0.0003040264,0.0005092159,0.0004551014,0.002162121,0.007156514,0.001416676,0.007493782,0.001124507,0.04726257],"study_design_scores_gemma":[0.000008546782,0.00008105233,0.9846922,0.00004170713,0.0001877192,0.00008893924,0.00218019,0.008775983,0.00039886,0.001467063,0.002055621,0.00002205997],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912084,0.0004110701,0.001903758,0.0001524356,0.000008263957,0.00002466207,0.000206618,0.00001067652,0.006074099],"genre_scores_gemma":[0.9988978,0.0001935536,0.0004241298,0.000009832971,0.000004250964,0.000009781073,0.0001353421,0.000001595065,0.0003236867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02526521,"threshold_uncertainty_score":0.05023628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03030780187784579,"score_gpt":0.2324194586858319,"score_spread":0.2021116568079861,"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."}}