{"id":"W2523835372","doi":"","title":"Optimal Control of Li-Ion Hydrogen Fuel Cell Hybrid Vehicles","year":2012,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo","keywords":"Fuel cells; Hydrogen; Automotive engineering; Hydrogen fuel; Ion; Control (management); Engineering; Computer science; Chemistry; Chemical engineering; Organic chemistry; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007338554,0.0008222712,0.0007513618,0.0003400437,0.0004727918,0.001731736,0.0006097535,0.0006828022,0.00221229],"category_scores_gemma":[0.001060294,0.0004189498,0.0004099417,0.0002241209,0.0008400373,0.0004212832,0.0008475258,0.0007867069,0.0002739958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130372,"about_ca_system_score_gemma":0.001299906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01761421,"about_ca_topic_score_gemma":0.008854571,"domain_scores_codex":[0.9997255,0.00007157071,0.00001057137,0.00005984841,0.00006772232,0.0000647649],"domain_scores_gemma":[0.999631,0.0001749858,0.00006412382,0.000009557515,0.000097621,0.00002266199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008913682,0.00003605192,0.0001818598,0.00006015301,0.00001509698,0.0000324447,0.00004628236,0.9862269,0.001718936,0.004933299,0.0005523511,0.006107518],"study_design_scores_gemma":[0.00001209894,0.00005591453,0.0001048933,0.000004448164,0.000003855175,0.000002392475,0.0000158221,0.9980725,0.0003948275,0.001004627,0.0003242886,0.000004263031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2110438,0.002554919,0.7106998,0.001041973,0.0003659934,0.0002289256,0.0002637688,0.0005673797,0.07323349],"genre_scores_gemma":[0.9856496,0.0004179917,0.007488167,0.00006390383,0.00002587369,0.00008263472,0.00006332048,0.0000207958,0.006187635],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01761421,"threshold_uncertainty_score":0.03502339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004982443172859948,"score_gpt":0.1634892484767731,"score_spread":0.1585068053039132,"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."}}