{"id":"W4362633722","doi":"10.1016/j.jairtraman.2023.102401","title":"A data-driven analysis of the aviation recovery from the COVID-19 pandemic","year":2023,"lang":"en","type":"article","venue":"Journal of Air Transport Management","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Natural Science Foundation of China","keywords":"Pandemic; Spell; Aviation; Coronavirus disease 2019 (COVID-19); Context (archaeology); Business; Aviation safety; Work (physics); Geography; Engineering; Medicine","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":[0.00170683,0.0002937157,0.0002843574,0.001227462,0.0003856189,0.001357585,0.0007624919,0.00118137,0.002068833],"category_scores_gemma":[0.006675388,0.0001724608,0.0005449431,0.001635953,0.000439413,0.0008811439,0.0006620832,0.001427946,0.0005661001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001201732,"about_ca_system_score_gemma":0.0006693942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03872213,"about_ca_topic_score_gemma":0.03512134,"domain_scores_codex":[0.9994243,0.0002342447,0.00003070976,0.00009427859,0.00009733385,0.0001190296],"domain_scores_gemma":[0.9951103,0.002800602,0.0006609366,0.0002883098,0.000700268,0.0004394915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001523948,0.00164462,0.6702856,0.0003639682,0.0004783172,0.002460928,0.001609078,0.2186496,0.004569891,0.0285159,0.03426147,0.03563673],"study_design_scores_gemma":[0.00006016539,0.0003779817,0.4879054,0.00006746383,0.0000741129,0.0003097104,0.003839112,0.4881706,0.001152119,0.006712073,0.01123646,0.0000947593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918107,0.0001738029,0.001258963,0.001315474,0.00002619639,0.00002610471,0.004010024,0.00005273467,0.001325979],"genre_scores_gemma":[0.9914125,0.0001159945,0.001311708,0.0001062247,0.00002977296,0.00002371316,0.006164102,0.00001815313,0.0008178958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03872213,"threshold_uncertainty_score":0.07699347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1144068313446093,"score_gpt":0.2846068514392042,"score_spread":0.170200020094595,"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."}}