{"id":"W3124157986","doi":"10.1111/caje.12255","title":"New vehicle feebates","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Economics/Revue canadienne d économique","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Ottawa","funders":"","keywords":"Benchmark (surveying); Welfare; Exploit; Economics; Function (biology); Public economics; Microeconomics; Computer science; Computer security; Market economy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001255211,0.0002522603,0.0004601848,0.000900197,0.000538666,0.00169374,0.0008184107,0.0005024725,0.006630432],"category_scores_gemma":[0.005712832,0.0001909149,0.0004765756,0.001889094,0.0004082248,0.0006541706,0.0003331895,0.0008167973,0.000592684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01312036,"about_ca_system_score_gemma":0.01216975,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6860996,"about_ca_topic_score_gemma":0.8464971,"domain_scores_codex":[0.9980987,0.0002385675,0.00006585901,0.000171574,0.0009040165,0.000521221],"domain_scores_gemma":[0.9968105,0.0006158245,0.0006679426,0.0002385463,0.001284311,0.0003829007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001251688,0.00045396,0.4053807,0.001045418,0.0005858714,0.0003764977,0.0008466813,0.2106398,0.005774162,0.06849802,0.1295657,0.1755814],"study_design_scores_gemma":[0.0001398523,0.0002346272,0.7140539,0.000118154,0.0001415867,0.0001291714,0.0009606311,0.05427242,0.003050742,0.007118264,0.2196768,0.0001038617],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7444326,0.001886796,0.01539085,0.002760683,0.0001836653,0.0008937544,0.09799144,0.0006604748,0.1357996],"genre_scores_gemma":[0.9623813,0.00033796,0.002652827,0.0001707049,0.00002460618,0.00009907954,0.01008897,0.00002970032,0.02421497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3139004,"threshold_uncertainty_score":0.6314979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08474865133149136,"score_gpt":0.1859371174006515,"score_spread":0.1011884660691601,"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."}}