{"id":"W2803498757","doi":"10.1080/1523908x.2018.1473152","title":"Local governance of greenhouse gas emissions from air travel","year":2018,"lang":"en","type":"article","venue":"Journal of Environmental Policy & Planning","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Svenska Forskningsrådet Formas; VINNOVA; Stiftelsen för Miljöstrategisk Forskning","keywords":"Greenhouse gas; Corporate governance; Quarter (Canadian coin); Natural resource economics; Business; Sustainable development; Environmental planning; Economics; Political science; Environmental science; Finance; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001268103,0.00008460329,0.0001913202,0.0007233098,0.001232283,0.003303934,0.0004840675,0.0003521172,0.003973121],"category_scores_gemma":[0.003287077,0.0001320284,0.0001830413,0.001329514,0.002094174,0.001123248,0.002254382,0.0003255302,0.00038492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003188126,"about_ca_system_score_gemma":0.001741532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02630975,"about_ca_topic_score_gemma":0.05096973,"domain_scores_codex":[0.9984359,0.0008671368,0.00004329042,0.0001800816,0.0001568827,0.0003166595],"domain_scores_gemma":[0.9983528,0.0004737283,0.0003914015,0.0001976073,0.0003391077,0.0002454791],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003480759,0.0003408835,0.5246348,0.0004833791,0.000340405,0.001893927,0.06705064,0.03597146,0.004616178,0.2405995,0.0139158,0.1098049],"study_design_scores_gemma":[0.00005055812,0.0002497997,0.6658676,0.0002524586,0.0001808654,0.0003290785,0.137349,0.02045936,0.00180437,0.06265075,0.1106767,0.0001293795],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9449428,0.0003108567,0.00261123,0.001394016,0.00001070829,0.00003907793,0.0001773211,0.00004878903,0.05046512],"genre_scores_gemma":[0.9984163,0.00005492297,0.0001498612,0.00002347603,0.000002091975,0.00000726911,0.00003251959,0.00000380904,0.001309682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02630975,"threshold_uncertainty_score":0.05231321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753236486640773,"score_gpt":0.2457398969197446,"score_spread":0.2182075320533369,"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."}}