{"id":"W2010753709","doi":"10.1016/j.jairtraman.2008.09.003","title":"Effects of competition and policy changes on Chinese airport productivity: An empirical investigation","year":2008,"lang":"en","type":"article","venue":"Journal of Air Transport Management","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":125,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Chinese University of Hong Kong; University of Hong Kong","keywords":"Data envelopment analysis; China; Competition (biology); Productivity; Business; Industrial organization; Aviation; Sample (material); Listing (finance); Stock (firearms); Economics; Finance; Engineering; Geography; Economic growth","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001114245,0.0004283166,0.0006107081,0.001823778,0.0009710884,0.001726595,0.0006194318,0.00102934,0.005066513],"category_scores_gemma":[0.00355504,0.0003086557,0.001176724,0.002704437,0.001298191,0.001184686,0.0008604907,0.001109553,0.0003661437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004205797,"about_ca_system_score_gemma":0.003432851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1211801,"about_ca_topic_score_gemma":0.1113412,"domain_scores_codex":[0.998909,0.0001554692,0.00007619239,0.0001873856,0.0002005691,0.0004714182],"domain_scores_gemma":[0.9932382,0.002644724,0.001971177,0.0002643519,0.0006478733,0.001233632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004518973,0.0004514935,0.9866262,0.00006027932,0.0002368543,0.0007781069,0.0007242903,0.003385003,0.000906659,0.00100996,0.0005853071,0.004783919],"study_design_scores_gemma":[0.00002468254,0.0001759712,0.9936581,0.000007142985,0.00014161,0.00005506692,0.001309658,0.003861311,0.0002406689,0.0001740664,0.000330119,0.00002161515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987914,0.0001412254,0.00004906927,0.0001061748,0.00000512085,0.000006505953,0.0001162306,0.000004011451,0.0007804072],"genre_scores_gemma":[0.9992607,0.0001087055,0.00001835801,0.000021542,0.000009561494,0.00000372501,0.0001751627,0.000001148087,0.000401128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1211801,"threshold_uncertainty_score":0.2409495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02836409300182444,"score_gpt":0.2503997026311738,"score_spread":0.2220356096293493,"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."}}