{"id":"W4406071802","doi":"10.1016/j.decarb.2024.100096","title":"Evaluating the economic and carbon emission reduction potential of fuel cell electric vehicle-to-grid","year":2025,"lang":"en","type":"article","venue":"DeCarbon","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Reduction (mathematics); Fuel cells; Grid; Carbon fibers; Electric vehicle; Automotive engineering; Environmental science; Environmental economics; Business; Natural resource economics; Computer science; Engineering; Economics; Power (physics); Physics; Geography; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001671491,0.0001118792,0.0001346656,0.0001251672,0.00004456922,0.00002031917,0.0001031576,0.0000815669,0.000004926673],"category_scores_gemma":[0.0000105714,0.00009115177,0.00003444177,0.0002507131,0.0000112219,0.0000322091,0.00002999389,0.0001742961,7.532943e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205588,"about_ca_system_score_gemma":0.00004857107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007903082,"about_ca_topic_score_gemma":0.000002062433,"domain_scores_codex":[0.9993381,0.00002848718,0.0002078412,0.0001578353,0.00009007318,0.0001776809],"domain_scores_gemma":[0.9997047,0.00002425481,0.00003759514,0.0001737345,0.00002183237,0.00003784258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002827745,0.000003962523,0.0003483021,0.00008861602,0.000020547,4.281917e-7,0.0001231863,0.04733014,0.9209767,0.00003699883,0.0003427373,0.03070012],"study_design_scores_gemma":[0.0002950493,0.0001247682,0.005664306,0.00002787892,0.000049734,0.000006471513,0.00003918733,0.7929249,0.1998362,0.0007219926,0.0001966896,0.0001128022],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992623,0.002105322,0.00004352714,0.00009869922,0.0004706153,0.0001737628,0.000001319289,0.0000551032,0.004428646],"genre_scores_gemma":[0.9994027,0.0001774209,0.0001183628,0.00002003069,0.0001668085,0.000007992534,0.000001973398,0.00001501909,0.00008970479],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7455947,"threshold_uncertainty_score":0.3717061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005469742984743436,"score_gpt":0.2331517331479994,"score_spread":0.227681990163256,"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."}}