{"id":"W2975248103","doi":"10.1016/j.enpol.2019.111001","title":"Effect of gasoline prices on car fuel efficiency: Evidence from Lebanon","year":2019,"lang":"en","type":"article","venue":"Energy Policy","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations","funders":"","keywords":"Gasoline; Sample (material); Economics; Alternative fuel vehicle; Empirical evidence; Fuel efficiency; Middle East; Econometrics; Automotive industry; Business; Alternative fuels; Engineering; Automotive engineering; Waste management; Diesel fuel; Geography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001780054,0.0003071473,0.0004190584,0.0002550613,0.00005258814,0.00001749934,0.0003549431,0.0001434367,0.0004622046],"category_scores_gemma":[0.00009776039,0.0002552023,0.0001771673,0.0003491394,0.0001155974,0.0001602615,0.00003217457,0.000111507,0.0002033791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007902575,"about_ca_system_score_gemma":0.00005930044,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05214236,"about_ca_topic_score_gemma":0.00121477,"domain_scores_codex":[0.9982075,0.0001518377,0.0003911725,0.0004251067,0.0004272885,0.0003970867],"domain_scores_gemma":[0.9983137,0.0006604769,0.0002256763,0.0006520637,0.00002159329,0.0001265155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006133713,0.0003437037,0.01480257,0.0002618639,0.0002610388,0.00001661841,0.002627038,0.4122391,0.1298369,0.426703,0.000336733,0.01195801],"study_design_scores_gemma":[0.002556328,0.002400217,0.06395545,0.000466894,0.0001513155,0.000002867969,0.00005933425,0.001636448,0.8473843,0.002070478,0.07846681,0.0008495147],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621239,0.0007822452,0.0001264481,0.0002458931,0.000235582,0.00008361638,0.00003123385,0.00009061642,0.03628051],"genre_scores_gemma":[0.9940768,0.0007704946,0.00007783746,0.0004997946,0.0004251357,0.00002709522,0.00006886027,0.00004911094,0.004004891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7175474,"threshold_uncertainty_score":0.99999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007705670464669738,"score_gpt":0.2523737164991657,"score_spread":0.2446680460344959,"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."}}