{"id":"W4285093626","doi":"10.1088/2634-4505/ac8071","title":"Does the metric matter? Climate change impacts of light-duty vehicle electrification in the US","year":2022,"lang":"en","type":"article","venue":"Environmental Research Infrastructure and Sustainability","topic":"Energy, Environment, and Transportation Policies","field":"Energy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Electrification; Greenhouse gas; Radiative forcing; Climate change; Environmental science; Global warming; Climate change mitigation; Metric (unit); Electricity; Environmental economics; Business; Engineering; Economics; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.001853272,0.0001492772,0.0001613655,0.0001957232,0.0006507401,0.00003542963,0.0004007087,0.00005725193,0.0005280865],"category_scores_gemma":[0.00007567912,0.0000773417,0.00006217316,0.0005875626,0.0004528505,0.0001641249,0.0001263354,0.0005919629,0.000003022105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004683128,"about_ca_system_score_gemma":0.0000324546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001804488,"about_ca_topic_score_gemma":0.0002594908,"domain_scores_codex":[0.9970543,0.0009729523,0.0003175585,0.0003201791,0.000792327,0.0005427124],"domain_scores_gemma":[0.9989977,0.000296593,0.00009474041,0.0005293054,0.00001331948,0.00006828862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000200835,0.0003665409,0.9582882,0.0001239348,0.00002527346,0.00001247037,0.0122982,0.001449332,0.003522756,0.007286997,0.0001199194,0.01630554],"study_design_scores_gemma":[0.0003352581,0.0001231229,0.9582166,0.000001786084,0.000009332918,0.000003543741,0.01220663,0.00005519893,0.002600217,0.01498794,0.01136955,0.00009083286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946483,0.0004472274,0.000002862766,0.003648896,0.00003249689,0.0006298494,0.00005772744,0.000007620799,0.0005250358],"genre_scores_gemma":[0.9985412,0.0006044372,0.000006523062,0.0003310003,0.00004485821,0.0003514423,0.00004293631,0.00001528439,0.00006234334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01621471,"threshold_uncertainty_score":0.5782177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01018959177361459,"score_gpt":0.2779094380055042,"score_spread":0.2677198462318896,"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."}}