{"id":"W2896990752","doi":"10.5430/bmr.v7n4p9","title":"The Effect of New Energy Vehicle Policies on Traffic Congestion: Evidence from Beijing","year":2018,"lang":"en","type":"article","venue":"Business and Management Research","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Social Science Fund of China","keywords":"Beijing; Traffic congestion; Traffic flow (computer networking); Transport engineering; Lottery; Environmental economics; Congestion pricing; Business; Computer science; Economics; Microeconomics; Geography; Engineering; China; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001031572,0.000320309,0.0005151041,0.0008152366,0.0004878432,0.000963747,0.0006654375,0.0005011508,0.001877064],"category_scores_gemma":[0.003944011,0.0002690925,0.0006343029,0.001627606,0.0009973006,0.0009973908,0.0008136042,0.0007071249,0.0001890706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002710625,"about_ca_system_score_gemma":0.001103943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09781948,"about_ca_topic_score_gemma":0.09833519,"domain_scores_codex":[0.9989323,0.000480291,0.00007391531,0.0001299241,0.0001873058,0.0001961543],"domain_scores_gemma":[0.9956388,0.001512434,0.001517277,0.000349384,0.0005903858,0.0003916883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009751375,0.0008878317,0.924488,0.0002679102,0.0009994758,0.001093193,0.0009326423,0.03727506,0.001051773,0.004308926,0.003307594,0.0244125],"study_design_scores_gemma":[0.0001178634,0.0003929338,0.9719935,0.00003534667,0.0003592063,0.00006673999,0.00137739,0.020856,0.0007881996,0.0009230075,0.003045109,0.00004469061],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997118,0.0003567052,0.0001506715,0.000292121,0.000008972912,0.0000136759,0.0002469331,0.000009265746,0.00180382],"genre_scores_gemma":[0.9991071,0.0002808496,0.00003268454,0.00003104294,0.000005663419,0.000008070811,0.0002480189,0.00000145077,0.0002850072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09781948,"threshold_uncertainty_score":0.1945002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02374527539600891,"score_gpt":0.2890036025780104,"score_spread":0.2652583271820015,"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."}}