{"id":"W2934740781","doi":"10.5539/ibr.v12n4p153","title":"Economic Cost Analysis of New Energy Vehicle Policy -Empirical Research Based on Beijing’s Data","year":2019,"lang":"en","type":"article","venue":"International Business Research","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Social Science Fund of China","keywords":"Beijing; Subsidy; Energy consumption; Environmental economics; Energy policy; Consumption (sociology); Business; Government (linguistics); Transport engineering; Economics; Renewable energy; Engineering; China; Market economy","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":[0.001896118,0.0005768863,0.0007903791,0.002949741,0.0003803317,0.00145982,0.0009869975,0.0005939637,0.003961137],"category_scores_gemma":[0.009757003,0.0003663501,0.001036121,0.004840678,0.0005934691,0.001982209,0.0007366678,0.001330485,0.000447457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005175007,"about_ca_system_score_gemma":0.001473873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07143299,"about_ca_topic_score_gemma":0.03815622,"domain_scores_codex":[0.9984424,0.0004161644,0.0001753263,0.0001999034,0.0004598277,0.0003065281],"domain_scores_gemma":[0.9916328,0.004433101,0.002016417,0.0005394213,0.001019863,0.0003583486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006095346,0.0004778254,0.7955394,0.0003573175,0.0006520464,0.0006308171,0.0002497637,0.1695316,0.0004260473,0.007332769,0.005968448,0.01822446],"study_design_scores_gemma":[0.00008422462,0.0002616442,0.8237579,0.00003947724,0.0002389241,0.0001409952,0.0007927126,0.16751,0.0009630672,0.001432752,0.004708556,0.00006968941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890003,0.0006222873,0.0008842499,0.000336634,0.00001299398,0.00008048139,0.005349315,0.00003667497,0.003677011],"genre_scores_gemma":[0.991349,0.0003450374,0.0002627651,0.00002771458,0.00001439229,0.00007052998,0.006651265,0.000009199548,0.001270009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07143299,"threshold_uncertainty_score":0.1420345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1667945201249283,"score_gpt":0.455767605802108,"score_spread":0.2889730856771797,"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."}}