{"id":"W4387216971","doi":"10.59720/22-035","title":"Exponential regression analysis of the Canadian Zero Emission Vehicle market’s effects on climate emissions in 2030","year":2023,"lang":"en","type":"article","venue":"Journal of Emerging Investigators","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subsidy; Government (linguistics); Climate change; Greenhouse gas; Natural resource economics; Business; Market share; Environmental economics; Environmental science; Economics; Marketing; Market economy","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":[0.004585529,0.0006874114,0.000657009,0.001115378,0.0007886089,0.001923868,0.001283018,0.0008076386,0.00868109],"category_scores_gemma":[0.01268394,0.0002514604,0.001265765,0.001284708,0.000975997,0.001040356,0.0006834467,0.00266424,0.0007040355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008171036,"about_ca_system_score_gemma":0.01003947,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8498865,"about_ca_topic_score_gemma":0.7398747,"domain_scores_codex":[0.9988123,0.0002900184,0.00003141242,0.0001932145,0.000257575,0.0004154512],"domain_scores_gemma":[0.9928738,0.004234916,0.0005921063,0.000222647,0.001770769,0.0003057169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001412621,0.000356139,0.1512274,0.0003390269,0.0005069906,0.0006316699,0.0006093248,0.6545576,0.002480211,0.09974257,0.02917814,0.05895819],"study_design_scores_gemma":[0.00004626431,0.0001194723,0.06487501,0.00003033402,0.0001331153,0.00004439515,0.0005880558,0.9214861,0.0008489629,0.005241883,0.006522469,0.00006388903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9369712,0.001709645,0.0177623,0.00311986,0.0001239114,0.0001337751,0.005066333,0.0003834004,0.03472968],"genre_scores_gemma":[0.9860173,0.0004584712,0.001580475,0.0001559807,0.00002766972,0.00002492443,0.00178814,0.00004191592,0.009905188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1501135,"threshold_uncertainty_score":0.301995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01282815193181589,"score_gpt":0.2446342304863021,"score_spread":0.2318060785544862,"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."}}