{"id":"W2038578252","doi":"10.4271/2014-01-1827","title":"A Study on How to Utilize Hilly Road Information in Equivalent Consumption Minimization Strategy of FCHEVs","year":2014,"lang":"en","type":"article","venue":"SAE International journal of alternative powertrains","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Minification; Consumption (sociology); Computer science; Transport engineering; Environmental economics; Engineering; Economics; World Wide Web; Social science","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":[0.0003884184,0.0001504538,0.0002425716,0.0008847721,0.00001377076,0.0000643155,0.0004304505,0.00005093977,0.0000194352],"category_scores_gemma":[0.0003420635,0.0001387027,0.00007013291,0.0001739648,0.00003314092,0.0006281305,0.00003597472,0.0002477486,0.00001057943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00023939,"about_ca_system_score_gemma":0.00003258834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000180529,"about_ca_topic_score_gemma":0.00003973541,"domain_scores_codex":[0.9985189,0.00005530848,0.000586342,0.00009141672,0.0005918941,0.0001561617],"domain_scores_gemma":[0.9989793,0.0000994248,0.0003116774,0.0001077389,0.0004488467,0.0000530436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009397174,0.0012503,0.04515503,0.00007682629,0.001180315,0.0001178875,0.01122257,0.2978425,0.01077872,0.00920985,0.001251148,0.6209751],"study_design_scores_gemma":[0.006407302,0.004099359,0.9163736,0.000679083,0.00004651064,0.00009685468,0.003762407,0.0399261,0.02488518,0.002096882,0.00111762,0.0005091645],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844612,0.00003861869,0.01332744,0.0004843783,0.0005290033,0.0002167244,0.00001641692,0.00004285444,0.0008833985],"genre_scores_gemma":[0.9993499,0.0001325849,0.0003303348,0.00006600808,0.00008651814,0.00000669031,0.000006351581,0.0000117124,0.000009915949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8712185,"threshold_uncertainty_score":0.565613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03123450931333304,"score_gpt":0.2954508859708402,"score_spread":0.2642163766575071,"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."}}