{"id":"W3008729079","doi":"10.1016/j.jpowsour.2020.227948","title":"Optimal energy management with balanced fuel economy and battery life for large hybrid electric mining truck","year":2020,"lang":"en","type":"article","venue":"Journal of Power Sources","topic":"Advanced Battery Technologies Research","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Truck; Battery (electricity); Energy management; Automotive engineering; Engineering; Business; Energy (signal processing); Environmental science; Power (physics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0003157929,0.0004474099,0.0007859048,0.0003547416,0.0005055146,0.001017609,0.0005791901,0.0007208192,0.001846163],"category_scores_gemma":[0.0005590724,0.0003808645,0.0003083769,0.0003671021,0.0003127315,0.0007496875,0.0005292991,0.0003377555,0.0001755409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007576073,"about_ca_system_score_gemma":0.0005914862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004351624,"about_ca_topic_score_gemma":0.005415602,"domain_scores_codex":[0.9998858,0.00002481929,0.000005397166,0.00002131244,0.00002423044,0.00003845077],"domain_scores_gemma":[0.9998292,0.00007687684,0.00002217597,0.000007424088,0.0000479451,0.00001637261],"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":[0.0003450861,0.0001228947,0.0007019213,0.00007645129,0.00003540911,0.0001344152,0.00004249372,0.9723221,0.008200568,0.002292786,0.0006651002,0.01506069],"study_design_scores_gemma":[0.0000179363,0.00007178847,0.0003481169,0.00000310676,0.00001078671,0.00001192166,0.00004419985,0.9973575,0.000666649,0.001236968,0.0002257022,0.000005254258],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6873932,0.00101009,0.2919835,0.0007917752,0.00009289436,0.0001465704,0.0001700724,0.0002417408,0.0181701],"genre_scores_gemma":[0.9965744,0.00004601505,0.002230902,0.0000122176,0.000006773628,0.00001558891,0.0000177206,0.000007425964,0.001088978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004351624,"threshold_uncertainty_score":0.008652568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008290239606084217,"score_gpt":0.2128930818254391,"score_spread":0.2046028422193549,"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."}}