{"id":"W3209964888","doi":"10.5281/zenodo.3982990","title":"Repository: Electrification of light-duty vehicle fleet alone will not meet mitigation targets.","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Electrification; Business; Duty; Automotive engineering; Transport engineering; Environmental science; Environmental economics; Engineering; Electricity; Economics; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.003056638,0.001703965,0.00236464,0.005104999,0.0007246345,0.00475673,0.004243728,0.003185849,0.1973132],"category_scores_gemma":[0.0227297,0.0009060752,0.001209649,0.01331578,0.0004049643,0.00315968,0.00249014,0.002071963,0.1291215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002481502,"about_ca_system_score_gemma":0.006473265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02447176,"about_ca_topic_score_gemma":0.03055279,"domain_scores_codex":[0.9960101,0.0002808064,0.0005212282,0.0003251399,0.002596038,0.0002667721],"domain_scores_gemma":[0.97552,0.005870325,0.001831153,0.002778428,0.01325378,0.0007462296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001228004,0.00004232001,0.0009399906,0.001450022,0.00006306927,0.0000352168,0.00001828847,0.001331999,0.000298417,0.001674603,0.98391,0.0101133],"study_design_scores_gemma":[0.0003009726,0.00008042696,0.005148933,0.0009902823,0.00009872996,0.00006058077,0.0000794892,0.00163603,0.002607037,0.004454588,0.9844548,0.00008824131],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0001430898,0.00008574779,0.0003405668,0.0003096611,0.0001956433,0.00002779921,0.9919098,0.001350648,0.005636968],"genre_scores_gemma":[0.002146892,0.0004289326,0.001103466,0.0001631853,0.00005967377,0.000128499,0.9900768,0.0008912628,0.005001324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1973132,"threshold_uncertainty_score":0.6600785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01904340621362033,"score_gpt":0.2179294927165696,"score_spread":0.1988860865029493,"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."}}