{"id":"W4400989687","doi":"10.69554/oibc8419","title":"Can airports be a catalyst for reducing aviation’s effect on the climate?","year":2024,"lang":"en","type":"article","venue":"Journal of airport management","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Berger (Canada)","funders":"","keywords":"Scope (computer science); Aviation; Incentive; Business; Aerospace; Environmental economics; Transport engineering; Engineering; Computer science; Economics","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":[0.00203018,0.0001243248,0.0002990083,0.0003981207,0.0001599579,0.0001641851,0.0001829816,0.0000471344,0.0002671109],"category_scores_gemma":[0.00004286616,0.00009078993,0.0003482706,0.0002906159,0.00001628814,0.0001471382,0.00003383497,0.00017817,0.00004504736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001713188,"about_ca_system_score_gemma":0.0000144558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001686742,"about_ca_topic_score_gemma":0.000006561809,"domain_scores_codex":[0.9986916,0.00001329121,0.0008059442,0.0002110372,0.00009675709,0.0001813643],"domain_scores_gemma":[0.9989256,0.00009378469,0.0006625776,0.000227068,0.00003733694,0.00005367771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005451503,0.0001436253,0.01677365,0.0002944378,0.001768669,0.0001876592,0.0004713591,0.002570712,0.000003593312,0.8438908,0.1220407,0.01180019],"study_design_scores_gemma":[0.001551048,0.001503149,0.05515234,0.0007234982,0.0009612305,0.00009472717,0.0006581689,0.008618315,0.0004056724,0.04339316,0.8861843,0.0007544257],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5427533,0.005456018,0.02080526,0.1886759,0.01009874,0.002486707,0.0006496647,0.0001817171,0.2288926],"genre_scores_gemma":[0.9957808,0.0001201669,0.0001428996,0.0003528757,0.0003160607,0.00003446222,0.00002342855,0.00001759261,0.003211774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8004977,"threshold_uncertainty_score":0.3702306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03136213157862433,"score_gpt":0.2487142767666933,"score_spread":0.217352145188069,"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."}}