{"id":"W4200481758","doi":"10.3390/wevj12040257","title":"Parametric Predictions for Pure Electric Vehicles","year":2021,"lang":"en","type":"article","venue":"World Electric Vehicle Journal","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Mean squared error; Artificial neural network; Parametric statistics; Root mean square; Approximation error; Mean absolute percentage error; Mean absolute error; Electric vehicle; Parametric model; Standard deviation; Mean square; Computer science; Algorithm; Mathematics; Statistics; Engineering; Artificial intelligence; Physics; Thermodynamics","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":[0.0002859777,0.0002330321,0.0002958214,0.001341145,0.0003942189,0.000178162,0.0004204979,0.0001403883,0.0001091393],"category_scores_gemma":[0.0004879864,0.0002388342,0.0001834378,0.006479044,0.00002500025,0.0002965072,0.00005051466,0.001399101,0.00004107055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005536165,"about_ca_system_score_gemma":0.0001685998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.274083e-7,"about_ca_topic_score_gemma":0.00001205604,"domain_scores_codex":[0.9978039,0.00005209887,0.0004372894,0.0002758749,0.0004242582,0.001006556],"domain_scores_gemma":[0.9987059,0.0003916705,0.00007205241,0.0003426004,0.0002957053,0.0001920851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006756064,0.0002427711,0.003437841,0.0001177544,0.0004417338,0.0002742105,0.00003515064,0.07971143,0.3090366,0.001279792,0.1012877,0.5040675],"study_design_scores_gemma":[0.002163893,0.0004418811,0.009643451,0.00006745558,0.0001180782,0.001647721,0.00007670517,0.5732923,0.2850389,0.02296251,0.1036655,0.0008815451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5995623,0.02718242,0.359665,0.003703851,0.001109239,0.0008962302,0.00002744133,0.002562717,0.005290705],"genre_scores_gemma":[0.9925373,0.002061881,0.003081189,0.0001027737,0.0004118031,0.00008760724,0.000006449385,0.00008253298,0.001628532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5031859,"threshold_uncertainty_score":0.9739377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01548788492317251,"score_gpt":0.2645495092449379,"score_spread":0.2490616243217653,"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."}}